crossfile_context_retrievalwref dict | prompt stringlengths 252 32.6k | right_context stringlengths 0 81.2k | metadata dict | crossfile_context_retrieval dict | groundtruth stringlengths 5 208 |
|---|---|---|---|---|---|
{
"list": [
{
"filename": "training_pipeline/modules/signatures.py",
"retrieved_chunk": " pred_source = tf.gather(params=labels, indices=indices)\n probs = tf.nn.softmax(predictions.logits, axis=1)\n pred_confidence = tf.reduce_max(probs, axis=1)\n return {\"label\": pred_s... | import tarfile
import wandb
import gradio as gr
import numpy as np
from PIL import Image
import tensorflow as tf
from transformers import ViTFeatureExtractor
PRETRAIN_CHECKPOINT = "google/vit-base-patch16-224-in21k"
feature_extractor = ViTFeatureExtractor.from_pretrained(PRETRAIN_CHECKPOINT)
MODEL = None
RESOLTUIO... |
wb_token_if = gr.Textbox(interactive=True, label="Your Weight & Biases API Key")
with gr.Row():
image_if = gr.Image()
label_if = gr.Label(num_top_classes=3)
classify_if = gr.Button()
classify_if.click(
get_predictions,
[wb_token_if, image_if],
label_if
)
... | {
"context_start_lineno": 0,
"file": "training_pipeline/huggingface/apps/gradio/app.py",
"groundtruth_start_lineno": 66,
"repository": "deep-diver-TFX-WandB-05c63c4",
"right_context_start_lineno": 67,
"task_id": "project_cc_python/2754"
} | {
"list": [
{
"filename": "training_pipeline/modules/signatures.py",
"retrieved_chunk": " any data of the type of tf.Example which is denoted as the type of sta\n ndard_artifacts.Examples in TFX. The purpose of this function is to ap\n ply Transform Graph obtained from Transform component to ... | Markdown("## Simple demo for a Image Classification of the Beans Dataset with HF ViT model") |
{
"list": [
{
"filename": "story_development/test_characters.py",
"retrieved_chunk": "- However, when Juan encounters a large butterfly, he becomes scared and runs away, leaving the butterfly in danger. The Butterfly Keeper tells Juan that having a fear of butterflies is okay, but he must learn to emp... | import openai
import os
from dotenv import load_dotenv
from ga.individual import Individual
from story_development.characters import Characters
load_dotenv()
openai.api_key = os.environ["OPENAI_API_KEY"]
conditioning_info = "target audience is a 5 year old boy.The story should help the reader overcome a fear of but... | {
"context_start_lineno": 0,
"file": "story_development/test_apply_recommendation.py",
"groundtruth_start_lineno": 54,
"repository": "knexer-ai-storyteller-86da1d3",
"right_context_start_lineno": 55,
"task_id": "project_cc_python/2743"
} | {
"list": [
{
"filename": "story_development/test_characters.py",
"retrieved_chunk": "- However, when Juan encounters a large butterfly, he becomes scared and runs away, leaving the butterfly in danger. The Butterfly Keeper tells Juan that having a fear of butterflies is okay, but he must learn to emp... | apply_recommendation(characters, recommendation, verbose=True)) | |
{
"list": [
{
"filename": "ideation.py",
"retrieved_chunk": "Client constraints:\n{self.conditioning_info}\nEach idea should have a title and a 2-3 sentence premise mentioning the protagonist, the setting, and the conflict, while also highlighting what makes the story interesting.\nHere's an example o... | import os
import sys
from collections import defaultdict
from fuzzywuzzy import fuzz
import openai
from dotenv import load_dotenv
from ideation import Ideation
from filter_ideas import filter_ideas
from outline_story import Outliner
from draft_story import Drafter
from story_development.development_ga import Developm... |
print_numbered_list("Generated ideas", ideas)
# Find the best ideas
most_creative = filter_ideas(
ideas, "most creative, surprising, and unexpected ideas that excite the imagination"
)
print_numbered_list("Most creative ideas", most_creative)
best_fit = filter_ideas(
ideas, "ideas that best fit the client's ... | {
"context_start_lineno": 0,
"file": "write_story.py",
"groundtruth_start_lineno": 40,
"repository": "knexer-ai-storyteller-86da1d3",
"right_context_start_lineno": 41,
"task_id": "project_cc_python/2738"
} | {
"list": [
{
"filename": "story_development/test_setting.py",
"retrieved_chunk": "- Juan, a curious and adventurous 5-year-old boy who loves catching butterflies.\n- Abuela, Juan's grandmother, who is wise and caring. She is concerned about the butterflies' welfare and wants to teach Juan about their... | make_ideas(3) |
{
"list": [
{
"filename": "story_development/test_outline.py",
"retrieved_chunk": "- However, when Juan encounters a large butterfly, he becomes scared and runs away, leaving the butterfly in danger. The Butterfly Keeper tells Juan that having a fear of butterflies is okay, but he must learn to empath... | import openai
import os
from dotenv import load_dotenv
from story_development.development_ga import DevelopmentGA
load_dotenv()
openai.api_key = os.environ["OPENAI_API_KEY"]
conditioning_info = "target audience is a 5 year old boy.The story should help the reader overcome a fear of butterflies."
premise = "\"The Bu... | {
"context_start_lineno": 0,
"file": "story_development/test_feedback.py",
"groundtruth_start_lineno": 51,
"repository": "knexer-ai-storyteller-86da1d3",
"right_context_start_lineno": null,
"task_id": "project_cc_python/2752"
} | {
"list": [
{
"filename": "story_development/test_apply_recommendation.py",
"retrieved_chunk": "recommendation = \"\"\"Combine Abuela and the Butterfly Keeper into one character - a wise, caring grandmother who is also an expert on butterflies. This would reduce redundancy and make her character more ... | get_feedback(outline, verbose=True) | |
{
"list": [
{
"filename": "pitching/pick_best_idea.py",
"retrieved_chunk": " print_numbered_list(\"Cutest\", cutest)\n selected_title = max(combined_vote_counts.items(), key=lambda x: x[1])[0]\n # Find the idea that best matches the selected title\n matches: Iterable[tuple[str, float]] = [... | import os
import sys
from collections import defaultdict
from fuzzywuzzy import fuzz
import openai
from dotenv import load_dotenv
from ideation import Ideation
from filter_ideas import filter_ideas
from outline_story import Outliner
from draft_story import Drafter
from story_development.development_ga import Developm... |
print("\n\nNotes:\n\n")
print(initial_ideas[0])
ga = DevelopmentGA(conditioning_info, premise, initial_ideas)
best_individual = ga.evolve(0, 1, 2)
stories = Drafter(conditioning_info, best_individual.get_notes()).draft()
print(f"\nPotential stories:\n")
print("\n\n========\n\n".join(story for story in stories))
# W... | {
"context_start_lineno": 0,
"file": "write_story.py",
"groundtruth_start_lineno": 77,
"repository": "knexer-ai-storyteller-86da1d3",
"right_context_start_lineno": 78,
"task_id": "project_cc_python/2739"
} | {
"list": [
{
"filename": "pitching/pick_best_idea.py",
"retrieved_chunk": " return selected_idea\nregistry = FunctionRegistry()\ninit_most_creative_id = registry.register(init_most_creative)\ninit_best_fit_id = registry.register(init_best_fit)\ninit_cutest_id = registry.register(init_cutest)\nweig... | outline(1) |
{
"list": [
{
"filename": "story_development/test_feedback.py",
"retrieved_chunk": "- However, when Juan encounters a large butterfly, he becomes scared and runs away, leaving the butterfly in danger. The Butterfly Keeper tells Juan that having a fear of butterflies is okay, but he must learn to empat... | import openai
import os
from dotenv import load_dotenv
from story_development.characters import Characters
load_dotenv()
openai.api_key = os.environ["OPENAI_API_KEY"]
conditioning_info = "target audience is a 5 year old boy.The story should help the reader overcome a fear of butterflies."
premise = '"The Butterfly ... |
recommendation = characters.make_recommendation(verbose=True)
| {
"context_start_lineno": 0,
"file": "story_development/test_characters.py",
"groundtruth_start_lineno": 51,
"repository": "knexer-ai-storyteller-86da1d3",
"right_context_start_lineno": 52,
"task_id": "project_cc_python/2748"
} | {
"list": [
{
"filename": "story_development/test_apply_recommendation.py",
"retrieved_chunk": "recommendation = \"\"\"Combine Abuela and the Butterfly Keeper into one character - a wise, caring grandmother who is also an expert on butterflies. This would reduce redundancy and make her character more ... | score(verbose=True, n=1) |
{
"list": [
{
"filename": "pitching/pick_best_idea.py",
"retrieved_chunk": " print_numbered_list(\"Cutest\", cutest)\n selected_title = max(combined_vote_counts.items(), key=lambda x: x[1])[0]\n # Find the idea that best matches the selected title\n matches: Iterable[tuple[str, float]] = [... | import os
import sys
from collections import defaultdict
from fuzzywuzzy import fuzz
import openai
from dotenv import load_dotenv
from ideation import Ideation
from filter_ideas import filter_ideas
from outline_story import Outliner
from draft_story import Drafter
from story_development.development_ga import Developm... |
stories = Drafter(conditioning_info, best_individual.get_notes()).draft()
print(f"\nPotential stories:\n")
print("\n\n========\n\n".join(story for story in stories))
# Write a more detailed story description
# Split the story up into pages, each with a couple lines of story and a brief image description.
# Produce a... | {
"context_start_lineno": 0,
"file": "write_story.py",
"groundtruth_start_lineno": 82,
"repository": "knexer-ai-storyteller-86da1d3",
"right_context_start_lineno": 83,
"task_id": "project_cc_python/2740"
} | {
"list": [
{
"filename": "pitching/pick_best_idea.py",
"retrieved_chunk": " return selected_idea\nregistry = FunctionRegistry()\ninit_most_creative_id = registry.register(init_most_creative)\ninit_best_fit_id = registry.register(init_best_fit)\ninit_cutest_id = registry.register(init_cutest)\nweig... | evolve(0, 1, 2) |
{
"list": [
{
"filename": "app/models.py",
"retrieved_chunk": " db.create_all()\n db.session.commit()\n # insert some test data\n conn = sqlite3.connect('app.db')\n print('opened database successfully')\n c = conn.cursor()\n sql_query = \"UPDATE paper SET meta_info_json_path = 'a... | import sqlite3
import time
from .gpt_utils import ArxivChatGPT
from .database_utils import sqlite_get_arxivID_by_paper_id
# The functions are used to interact with the database
def reply_message(user_id, arxivID, content):
# conn = sqlite3.connect('app.db')
# print('opened database successfully')
# c = c... |
return ret
def get_papers(pid):
#connect to database
conn = sqlite3.connect('app.db')
print('opened database successfully')
c = conn.cursor()
cursor = c.execute("SELECT * FROM paper where pid = " + str(pid))
for row in cursor:
cur_tup = (row[0])
return cur_tup
# delete a user... | {
"context_start_lineno": 0,
"file": "app/controller/_old_version.py",
"groundtruth_start_lineno": 18,
"repository": "husisy-arxiv-gpt-ef98efb",
"right_context_start_lineno": 19,
"task_id": "project_cc_python/2762"
} | {
"list": [
{
"filename": "app/models.py",
"retrieved_chunk": " c.execute(sql_query)\n conn.commit()\n # show the table\n contents = c.execute(\"SELECT * FROM paper\")",
"score": 87.55929677533274
},
{
"filename": "main_chat.py",
"retrieved_chunk": " # chatgpt.... | chat(content, tag_print=False, tag_return=True) |
{
"list": [
{
"filename": "app/models.py",
"retrieved_chunk": " db.create_all()\n db.session.commit()\n # insert some test data\n conn = sqlite3.connect('app.db')\n print('opened database successfully')\n c = conn.cursor()\n sql_query = \"UPDATE paper SET meta_info_json_path = 'a... | import sqlite3
import time
from .gpt_utils import ArxivChatGPT
from .database_utils import sqlite_get_arxivID_by_paper_id
# The functions are used to interact with the database
def reply_message(user_id, arxivID, content):
# conn = sqlite3.connect('app.db')
# print('opened database successfully')
# c = c... |
ret = chatgpt.chat(content, tag_print=False, tag_return=True)
return ret
def get_papers(pid):
#connect to database
conn = sqlite3.connect('app.db')
print('opened database successfully')
c = conn.cursor()
cursor = c.execute("SELECT * FROM paper where pid = " + str(pid))
for row in curs... | {
"context_start_lineno": 0,
"file": "app/controller/_old_version.py",
"groundtruth_start_lineno": 17,
"repository": "husisy-arxiv-gpt-ef98efb",
"right_context_start_lineno": 18,
"task_id": "project_cc_python/2761"
} | {
"list": [
{
"filename": "app/models.py",
"retrieved_chunk": " c.execute(sql_query)\n conn.commit()\n # show the table\n contents = c.execute(\"SELECT * FROM paper\")",
"score": 87.55929677533274
},
{
"filename": "app/routes.py",
"retrieved_chunk": "def make_admi... | select(arxivID, print_meta_info=False) |
{
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " (2) alphas: The attention tensor containing the weights for all\n genes.\n (3) gamma: A tensor containing the gene scores.\n Raises:\n None.\n \"\... | """Implementation of transfer learning for scANNA's projection model."""
from .base._constants_and_types import _DEVICE_TYPES
from .scanna_projection_attention import ProjectionAttention
import torch
class FineTuningModel(ProjectionAttention):
"""Pretrained scANNA model to be finetuned for a new data.
Attri... |
alphas = self._softmax(self.attention_module(input_tensor))
gamma = self._gene_scores(alphas, x_masked)
# The abbrevation "gse" stands for gene stacked event (gse), which
# is the output of the a projection block (with all branches).
gse = self._parallel_eva... | {
"context_start_lineno": 0,
"file": "scanna/model/finetuning_scanna_projection_attention.py",
"groundtruth_start_lineno": 84,
"repository": "SindiLab-scANNA-b65b3d8",
"right_context_start_lineno": 85,
"task_id": "project_cc_python/2715"
} | {
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " alphas = self._softmax(self.attention_module(input_tensor))\n gamma = self._gene_scores(alphas, x_masked)\n # The abbrevation \"gse\" stands for gene stacked event (gse), which is\n ... | _parallel_eval(self.masking_layer, input_tensor) |
{
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " (2) alphas: The attention tensor containing the weights for all\n genes.\n (3) gamma: A tensor containing the gene scores.\n Raises:\n None.\n \"\... | """Implementation of scANNA with additive attention."""
from .base._base_model import BaseNeuralAttentionModel
from .base._constants_and_types import _DEVICE_TYPES
import torch
class AdditiveModel(BaseNeuralAttentionModel):
"""Implementation of additive attention and scANNA from base class.
The additive at... |
return outputs, alphas, gene_scores
| {
"context_start_lineno": 0,
"file": "scanna/model/scanna_additive_attention.py",
"groundtruth_start_lineno": 59,
"repository": "SindiLab-scANNA-b65b3d8",
"right_context_start_lineno": 60,
"task_id": "project_cc_python/2721"
} | {
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " alphas = self._softmax(self.attention_module(input_tensor))\n gamma = self._gene_scores(alphas, x_masked)\n # The abbrevation \"gse\" stands for gene stacked event (gse), which is\n ... | _parallel_eval(self.network, gene_scores) |
{
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " (2) alphas: The attention tensor containing the weights for all\n genes.\n (3) gamma: A tensor containing the gene scores.\n Raises:\n None.\n \"\... | """Implementation of transfer learning for scANNA's projection model."""
from .base._constants_and_types import _DEVICE_TYPES
from .scanna_projection_attention import ProjectionAttention
import torch
class FineTuningModel(ProjectionAttention):
"""Pretrained scANNA model to be finetuned for a new data.
Attri... |
alphas = self._softmax(self.attention_module(input_tensor))
gamma = self._gene_scores(alphas, x_masked)
# The abbrevation "gse" stands for gene stacked event (gse), which
# is the output of the a projection block (with all branches).
gse = self._parallel_eva... | {
"context_start_lineno": 0,
"file": "scanna/model/finetuning_scanna_projection_attention.py",
"groundtruth_start_lineno": 84,
"repository": "SindiLab-scANNA-b65b3d8",
"right_context_start_lineno": 85,
"task_id": "project_cc_python/2716"
} | {
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " alphas = self._softmax(self.attention_module(input_tensor))\n gamma = self._gene_scores(alphas, x_masked)\n # The abbrevation \"gse\" stands for gene stacked event (gse), which is\n ... | masking_layer, input_tensor) |
{
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " (2) alphas: The attention tensor containing the weights for all\n genes.\n (3) gamma: A tensor containing the gene scores.\n Raises:\n None.\n \"\... | """Implementation of scANNA with additive attention."""
from .base._base_model import BaseNeuralAttentionModel
from .base._constants_and_types import _DEVICE_TYPES
import torch
class AdditiveModel(BaseNeuralAttentionModel):
"""Implementation of additive attention and scANNA from base class.
The additive at... |
gene_scores = self._gene_scores(alphas, x)
outputs = self._parallel_eval(self.network, gene_scores)
return outputs, alphas, gene_scores
| {
"context_start_lineno": 0,
"file": "scanna/model/scanna_additive_attention.py",
"groundtruth_start_lineno": 57,
"repository": "SindiLab-scANNA-b65b3d8",
"right_context_start_lineno": 58,
"task_id": "project_cc_python/2719"
} | {
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " alphas = self._softmax(self.attention_module(input_tensor))\n gamma = self._gene_scores(alphas, x_masked)\n # The abbrevation \"gse\" stands for gene stacked event (gse), which is\n ... | _softmax(self.attention(x)) |
{
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " (2) alphas: The attention tensor containing the weights for all\n genes.\n (3) gamma: A tensor containing the gene scores.\n Raises:\n None.\n \"\... | """Implementation of scANNA with additive attention."""
from .base._base_model import BaseNeuralAttentionModel
from .base._constants_and_types import _DEVICE_TYPES
import torch
class AdditiveModel(BaseNeuralAttentionModel):
"""Implementation of additive attention and scANNA from base class.
The additive at... |
outputs = self._parallel_eval(self.network, gene_scores)
return outputs, alphas, gene_scores
| {
"context_start_lineno": 0,
"file": "scanna/model/scanna_additive_attention.py",
"groundtruth_start_lineno": 58,
"repository": "SindiLab-scANNA-b65b3d8",
"right_context_start_lineno": 59,
"task_id": "project_cc_python/2720"
} | {
"list": [
{
"filename": "scanna/model/scanna_projection_attention.py",
"retrieved_chunk": " alphas = self._softmax(self.attention_module(input_tensor))\n gamma = self._gene_scores(alphas, x_masked)\n # The abbrevation \"gse\" stands for gene stacked event (gse), which is\n ... | _gene_scores(alphas, x) |
{
"list": [
{
"filename": "wvalidate/validator_return.py",
"retrieved_chunk": "\t\tif success:\n\t\t\tif errors is not None:\n\t\t\t\traise ValidatorReturnException(\"The \\\"errors\\\" property must be None, when the \\\"success\\\" property is True\")\n\t\t\tself._success = True\n\t\t\tself._errors ... | import pytest
from wvalidate.validator_return import ValidatorReturn, ValidatorReturnException
from wvalidate.validator_error import ValidatorError
@pytest.mark.parametrize("success", [None, "S2", [], 1, 1.3])
def test_validator_return_with_success_invalid(success):
with pytest.raises(ValidatorReturnException):
V... |
validator_return_error = ValidatorReturn(False, ValidatorError("Error1"))
assert validator_return_error.success == False
assert len(validator_return_error.errors) == 1
assert validator_return_error.errors[0] == ValidatorError("Error1")
validator_return_errors = ValidatorReturn(False, [
ValidatorError("Error1... | {
"context_start_lineno": 0,
"file": "tests/test_validator_return.py",
"groundtruth_start_lineno": 25,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 26,
"task_id": "project_cc_python/2776"
} | {
"list": [
{
"filename": "tests/validators/test_list_validator.py",
"retrieved_chunk": "\tassert ListValidator().is_valid(None) == get_error_is_not_list()\n\tassert ListValidator().is_valid(True) == get_error_is_not_list()\n\tassert ListValidator().is_valid(False) == get_error_is_not_list()\n\tassert... | errors == None |
{
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "from __future__ import annotations\nfrom typing import Optional, Union, List\nfrom .. import Validator, ValidatorReturn, ValidatorError, ValidatorPath\ndef isinstance_validator_or_list_validators(validators: object... | from wvalidate.validator import Validator
from wvalidate.validate import Validate as v
from wvalidate.validator_return import ValidatorReturn
class CustomValidator(Validator):
def is_valid(self, _data: object) -> ValidatorReturn:
return ValidatorReturn(True)
def test_nullable_validator_is_instance_validator():
... | {
"context_start_lineno": 0,
"file": "tests/test_validate.py",
"groundtruth_start_lineno": 17,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 18,
"task_id": "project_cc_python/2771"
} | {
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "\tfor validator in validators:\n\t\tif not isinstance(validator, Validator):\n\t\t\treturn False\n\treturn True\nclass ListValidatorException(Exception):\n pass\nclass ListValidator(Validator):\n def __init__(sel... | string(), Validator) == True | |
{
"list": [
{
"filename": "wvalidate/validator_error.py",
"retrieved_chunk": "from __future__ import annotations\nfrom .validator_path import ValidatorPath\nclass ValidatorErrorException(Exception):\n\tpass\nclass ValidatorError:\n\tdef __init__(self, message: str, path: ValidatorPath = None) -> None:... | import pytest
from wvalidate.validator_error import ValidatorError, ValidatorErrorException
from wvalidate.validator_path import ValidatorPath
@pytest.mark.parametrize("message", [None, True, False, list(), 1, 1.3])
def test_validator_error_with_message_invalid(message):
with pytest.raises(ValidatorErrorException):
... |
assert validator_error_without_path.path == ValidatorPath()
validator_error_without_path_again = ValidatorError('message', None)
assert validator_error_without_path_again.message == 'message'
assert validator_error_without_path_again.path == ValidatorPath()
validator_error_with_path = ValidatorError('message',... | {
"context_start_lineno": 0,
"file": "tests/test_validator_error.py",
"groundtruth_start_lineno": 17,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 18,
"task_id": "project_cc_python/2773"
} | {
"list": [
{
"filename": "wvalidate/validator_error.py",
"retrieved_chunk": "\t\tself.message = message\n\t\tself.path = path if path else ValidatorPath()\n\tdef __repr__(self) -> str:\n\t\treturn f\"ValidatorError(messae='{self.message}', path={self.path})\"\n\tdef __eq__(self, error: object) -> boo... | message == 'message' |
{
"list": [
{
"filename": "wvalidate/validators/nullable_validator.py",
"retrieved_chunk": "from __future__ import annotations\nfrom ..validator import Validator, ValidatorReturn\nclass NullableValidatorException(Exception):\n pass\nclass NullableValidator(Validator):\n def __init__(\n self,\n ... | import pytest
from wvalidate import Validator, ValidatorReturn, ValidatorError
from wvalidate.validators.nullable_validator import NullableValidator, NullableValidatorException
class CustomValidator(Validator):
def __init__(self, is_valid: bool) -> None:
super().__init__()
self.__is_valid = is_valid
def is_val... |
assert validator_with_custom_valid.is_valid("VALID") == ValidatorReturn(True)
assert validator_with_custom_invalid.is_valid(None) == ValidatorReturn(True)
assert validator_with_custom_invalid.is_valid("INVALID") == ValidatorReturn(False, ValidatorError("INVALID"))
| {
"context_start_lineno": 0,
"file": "tests/validators/test_nullable_validator.py",
"groundtruth_start_lineno": 41,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 42,
"task_id": "project_cc_python/2779"
} | {
"list": [
{
"filename": "wvalidate/validators/nullable_validator.py",
"retrieved_chunk": " raise NullableValidatorException(\"Expected a Validator\")\n super().__init__()\n self.__validator = validator\n def is_valid(self, data) -> ValidatorReturn:\n if data is None:\n return Val... | is_valid(None) == ValidatorReturn(True) |
{
"list": [
{
"filename": "wvalidate/validators/enum_validator.py",
"retrieved_chunk": "\t\tself.__options = options\n\tdef is_valid(self, data) -> ValidatorReturn:\n\t\tif data not in self.__options:\n\t\t\treturn ValidatorReturn(False, ValidatorError(f\"Is not among the options. {self.__options}\"))... | import pytest
from wvalidate import Validator, ValidatorReturn, ValidatorError
from wvalidate.validators.enum_validator import EnumValidator, EnumValidatorException
def test_enum_validator_is_instance_validator():
assert issubclass(EnumValidator, Validator) == True
def test_enum_validator_without_a_list_of_optio... |
def test_enum_validator_validate():
TESTS = [
(["ACTIVE", "DELETED"], "ACTIVE"),
(["ACTIVE", "DELETED"], "DELETED"),
([2, 3, 5], 2),
([False, True, None], None),
([None, "DELETED", 1], 1),
([41, None, 15, "DELETED", 31], 15),
]
for test, data in TESTS:
validator_return = ValidatorReturn(True)
ass... | {
"context_start_lineno": 0,
"file": "tests/validators/test_enum_validator.py",
"groundtruth_start_lineno": 31,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 32,
"task_id": "project_cc_python/2777"
} | {
"list": [
{
"filename": "wvalidate/validators/enum_validator.py",
"retrieved_chunk": "\t\tself.__options = options\n\tdef is_valid(self, data) -> ValidatorReturn:\n\t\tif data not in self.__options:\n\t\t\treturn ValidatorReturn(False, ValidatorError(f\"Is not among the options. {self.__options}\"))... | is_valid(data) == validator_return |
{
"list": [
{
"filename": "wvalidate/validator_error.py",
"retrieved_chunk": "from __future__ import annotations\nfrom .validator_path import ValidatorPath\nclass ValidatorErrorException(Exception):\n\tpass\nclass ValidatorError:\n\tdef __init__(self, message: str, path: ValidatorPath = None) -> None:... | import pytest
from wvalidate.validator_error import ValidatorError, ValidatorErrorException
from wvalidate.validator_path import ValidatorPath
@pytest.mark.parametrize("message", [None, True, False, list(), 1, 1.3])
def test_validator_error_with_message_invalid(message):
with pytest.raises(ValidatorErrorException):
... |
validator_error_without_path_again = ValidatorError('message', None)
assert validator_error_without_path_again.message == 'message'
assert validator_error_without_path_again.path == ValidatorPath()
validator_error_with_path = ValidatorError('message', ValidatorPath("test", 1))
assert validator_error_with_path.... | {
"context_start_lineno": 0,
"file": "tests/test_validator_error.py",
"groundtruth_start_lineno": 18,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 19,
"task_id": "project_cc_python/2774"
} | {
"list": [
{
"filename": "wvalidate/validator_error.py",
"retrieved_chunk": "\t\tself.message = message\n\t\tself.path = path if path else ValidatorPath()\n\tdef __repr__(self) -> str:\n\t\treturn f\"ValidatorError(messae='{self.message}', path={self.path})\"\n\tdef __eq__(self, error: object) -> boo... | path == ValidatorPath() |
{
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "from __future__ import annotations\nfrom typing import Optional, Union, List\nfrom .. import Validator, ValidatorReturn, ValidatorError, ValidatorPath\ndef isinstance_validator_or_list_validators(validators: object... | from wvalidate.validator import Validator
from wvalidate.validate import Validate as v
from wvalidate.validator_return import ValidatorReturn
class CustomValidator(Validator):
def is_valid(self, _data: object) -> ValidatorReturn:
return ValidatorReturn(True)
def test_nullable_validator_is_instance_validator():
... |
assert isinstance(v.numeric(), Validator) == True
assert isinstance(v.string(), Validator) == True
| {
"context_start_lineno": 0,
"file": "tests/test_validate.py",
"groundtruth_start_lineno": 15,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 16,
"task_id": "project_cc_python/2769"
} | {
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "\tfor validator in validators:\n\t\tif not isinstance(validator, Validator):\n\t\t\treturn False\n\treturn True\nclass ListValidatorException(Exception):\n pass\nclass ListValidator(Validator):\n def __init__(sel... | nullable(CustomValidator()), Validator) == True |
{
"list": [
{
"filename": "wvalidate/validators/email_validator.py",
"retrieved_chunk": "from .string_validator import StringValidator\nclass EmailValidator(StringValidator):\n def __init__(self) -> None:\n REGEX_EMAIL = r'^[\\w\\.-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)*\\.[a-zA-Z0-9_-]+$'\n supe... | import pytest
from wvalidate import Validator, ValidatorReturn, ValidatorError
from wvalidate.validators.string_validator import StringValidator, StringValidatorException
REGEX_ONLY_NUMBERS = r'^[0-9]+$'
REGEX_ONLY_LETTERS = r'^[a-zA-Z]+$'
def get_error_is_not_string() -> ValidatorReturn:
return ValidatorReturn(Fal... |
assert StringValidator().is_valid("TEST-100") == ValidatorReturn(True)
assert StringValidator().is_valid("") == ValidatorReturn(True)
assert StringValidator().is_valid(1) == get_error_is_not_string()
assert StringValidator().is_valid(1.5) == get_error_is_not_string()
assert StringValidator().is_valid(None) == ge... | {
"context_start_lineno": 0,
"file": "tests/validators/test_string_validator.py",
"groundtruth_start_lineno": 74,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 75,
"task_id": "project_cc_python/2778"
} | {
"list": [
{
"filename": "wvalidate/validators/email_validator.py",
"retrieved_chunk": "from .string_validator import StringValidator\nclass EmailValidator(StringValidator):\n def __init__(self) -> None:\n REGEX_EMAIL = r'^[\\w\\.-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)*\\.[a-zA-Z0-9_-]+$'\n supe... | is_valid("1") == ValidatorReturn(True) |
{
"list": [
{
"filename": "wvalidate/validators/email_validator.py",
"retrieved_chunk": "from .string_validator import StringValidator\nclass EmailValidator(StringValidator):\n def __init__(self) -> None:\n REGEX_EMAIL = r'^[\\w\\.-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)*\\.[a-zA-Z0-9_-]+$'\n supe... | import pytest
from wvalidate import Validator, ValidatorReturn, ValidatorError
from wvalidate.validators.email_validator import EmailValidator
VALID_EMAILS = [
r"example@example.com",
r"test.email@example.com",
r"john.doe@example.com",
r"jane_doe@example.com",
r"email123@example.com",
r"e-mail@example.com",
r"... |
@pytest.mark.parametrize("email_invalid", INVALID_EMAILS)
def test_email_validator_validate_email_invalid(email_invalid):
assert EmailValidator().is_valid(email_invalid) == ValidatorReturn(False, ValidatorError("Invalid email format."))
| {
"context_start_lineno": 0,
"file": "tests/validators/test_email_validator.py",
"groundtruth_start_lineno": 72,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 73,
"task_id": "project_cc_python/2783"
} | {
"list": [
{
"filename": "wvalidate/validators/email_validator.py",
"retrieved_chunk": "from .string_validator import StringValidator\nclass EmailValidator(StringValidator):\n def __init__(self) -> None:\n REGEX_EMAIL = r'^[\\w\\.-]+@[a-zA-Z0-9_-]+(\\.[a-zA-Z0-9_-]+)*\\.[a-zA-Z0-9_-]+$'\n supe... | is_valid(email_valid) == ValidatorReturn(True) |
{
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "from __future__ import annotations\nfrom typing import Optional, Union, List\nfrom .. import Validator, ValidatorReturn, ValidatorError, ValidatorPath\ndef isinstance_validator_or_list_validators(validators: object... | from wvalidate.validator import Validator
from wvalidate.validate import Validate as v
from wvalidate.validator_return import ValidatorReturn
class CustomValidator(Validator):
def is_valid(self, _data: object) -> ValidatorReturn:
return ValidatorReturn(True)
def test_nullable_validator_is_instance_validator():
... |
assert isinstance(v.string(), Validator) == True
| {
"context_start_lineno": 0,
"file": "tests/test_validate.py",
"groundtruth_start_lineno": 16,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 17,
"task_id": "project_cc_python/2770"
} | {
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "\tfor validator in validators:\n\t\tif not isinstance(validator, Validator):\n\t\t\treturn False\n\treturn True\nclass ListValidatorException(Exception):\n pass\nclass ListValidator(Validator):\n def __init__(sel... | numeric(), Validator) == True |
{
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": "\tfor validator in validators:\n\t\tif not isinstance(validator, Validator):\n\t\t\treturn False\n\treturn True\nclass ListValidatorException(Exception):\n pass\nclass ListValidator(Validator):\n def __init__(sel... | import pytest
from wvalidate import Validator, ValidatorReturn, ValidatorError, ValidatorPath
from wvalidate.validators.list_validator import ListValidator, ListValidatorException
from wvalidate.validators.integer_validator import IntegerValidator
from wvalidate.validators.float_validator import FloatValidator
from wv... |
assert ListValidator().is_valid([-100, "213"]) == ValidatorReturn(True)
assert ListValidator().is_valid(["200", None]) == ValidatorReturn(True)
assert ListValidator().is_valid("1") == get_error_is_not_list()
assert ListValidator().is_valid(None) == get_error_is_not_list()
assert ListValidator().is_valid(True) ==... | {
"context_start_lineno": 0,
"file": "tests/validators/test_list_validator.py",
"groundtruth_start_lineno": 38,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 39,
"task_id": "project_cc_python/2784"
} | {
"list": [
{
"filename": "wvalidate/validators/list_validator.py",
"retrieved_chunk": " super().__init__()\n if validators == None:\n self.__validators = []\n else:\n self.__validators = validators if isinstance(validators, list) else [validators]\n def is_valid(self, data: object... | is_valid([1]) == ValidatorReturn(True) |
{
"list": [
{
"filename": "tests/validators/test_list_validator.py",
"retrieved_chunk": "\tassert issubclass(ListValidator, Validator) == True\n@pytest.mark.parametrize(\"validators\", [\"S2\", True, False, 1, [], [1], [\"121\"]])\ndef test_validator_return_with_validators_invalid(validators):\n\twith... | import pytest
from wvalidate import Validator, ValidatorReturn, ValidatorError, ValidatorPath
from wvalidate.validators.dict_validator import DictValidator, DictValidatorException
from wvalidate.validators.string_validator import StringValidator
from wvalidate.validators.integer_validator import IntegerValidator
from ... |
assert DictValidator().is_valid({ "age": 22 }) == ValidatorReturn(True)
assert DictValidator().is_valid({ "users": []}) == ValidatorReturn(True)
assert DictValidator().is_valid("1") == get_return_error_is_not_dict()
assert DictValidator().is_valid(None) == get_return_error_is_not_dict()
assert DictValidator().is... | {
"context_start_lineno": 0,
"file": "tests/validators/test_dict_validator.py",
"groundtruth_start_lineno": 51,
"repository": "leandl-wvalidate-8cb9603",
"right_context_start_lineno": 52,
"task_id": "project_cc_python/2785"
} | {
"list": [
{
"filename": "tests/validators/test_list_validator.py",
"retrieved_chunk": "\tassert ListValidator().is_valid(None) == get_error_is_not_list()\n\tassert ListValidator().is_valid(True) == get_error_is_not_list()\n\tassert ListValidator().is_valid(False) == get_error_is_not_list()\n\tassert... | is_valid({}) == ValidatorReturn(True) |
{
"list": [
{
"filename": "zeronlg/evaluation/TranslateEvaluator.py",
"retrieved_chunk": " if output_path:\n self.log(f'Save translation results to {result_file}')\n json.dump(results, open(result_file, 'w'))\n if not no_score:\n scores = translate_eval(g... | import os
import json
import torch
import logging
from tqdm import tqdm
from torch.utils.data import DataLoader
from sentence_transformers import LoggingHandler
from typing import Dict, Any, Union
from .. import Framework, ZeroNLG
from ..datasets import CaptionDataset
from ..utils import coco_caption_eval
logging.ba... |
for k, v in coco_test.eval.items():
self.log(f'[{prefix}] {k} {v}')
score = coco_test.eval[self.monitor]
return score
| {
"context_start_lineno": 0,
"file": "zeronlg/evaluation/CaptionEvaluator.py",
"groundtruth_start_lineno": 116,
"repository": "yangbang18-ZeroNLG-bbd3f33",
"right_context_start_lineno": 117,
"task_id": "project_cc_python/2736"
} | {
"list": [
{
"filename": "zeronlg/evaluation/TranslateEvaluator.py",
"retrieved_chunk": " score = scores[self.monitor]\n return score",
"score": 103.35799230658446
},
{
"filename": "zeronlg/evaluation/RetrievalEvaluator.py",
"retrieved_chunk": " ... | eval, open(scores_file, 'w')) |
{
"list": [
{
"filename": "zeronlg/losses/LossManager.py",
"retrieved_chunk": " outputs = self.model(sentence_features)\n loss, loss_msg_dict = 0, {}\n for name in ['mse', 'at_teacher', 'at_student', 'contrastive']:\n this_loss, this_dict = getattr(self, f'forward_{name... | import os
import torch
import json
import time
import shutil
import logging
import datetime
import random
import numpy as np
import transformers
import stat
import tempfile
import torch
import torch.backends.cudnn as cudnn
from torch import nn
from torch.optim import Optimizer
from torch.utils.data import DataLoader
... |
optimizer.zero_grad()
if not skip_scheduler:
scheduler.step()
training_steps += 1
global_step += 1
if log_every > 0 and global_step % log_every == 0:
self.log_training_info(metric_log... | {
"context_start_lineno": 0,
"file": "zeronlg/Framework.py",
"groundtruth_start_lineno": 487,
"repository": "yangbang18-ZeroNLG-bbd3f33",
"right_context_start_lineno": 488,
"task_id": "project_cc_python/2732"
} | {
"list": [
{
"filename": "train.py",
"retrieved_chunk": "from zeronlg.models import Dense, Projector, Decoder, Transformer\nlogging.basicConfig(format='%(asctime)s - %(message)s',\n datefmt='%Y-%m-%d %H:%M:%S',\n level=logging.INFO,\n handlers=... | update(**loss_msg_dict) |
{
"list": [
{
"filename": "zeronlg/models/Transformer.py",
"retrieved_chunk": " self.auto_model = AutoModel.from_pretrained(model_name_or_path, config=config, cache_dir=cache_dir)\n def _load_t5_model(self, model_name_or_path, config, cache_dir=None):\n \"\"\"Loads the encoder mod... | import os
import torch
import json
import time
import shutil
import logging
import datetime
import random
import numpy as np
import transformers
import stat
import tempfile
import torch
import torch.backends.cudnn as cudnn
from torch import nn
from torch.optim import Optimizer
from torch.utils.data import DataLoader
... |
return [transformer_model, pooling_model]
def set_module_attribute(self, module_class, key, value):
for module in self.get_modules():
if isinstance(module, module_class):
setattr(module, key, value)
def get_module_attribute(self, key, default_value=None):
... | {
"context_start_lineno": 0,
"file": "zeronlg/Framework.py",
"groundtruth_start_lineno": 178,
"repository": "yangbang18-ZeroNLG-bbd3f33",
"right_context_start_lineno": 179,
"task_id": "project_cc_python/2731"
} | {
"list": [
{
"filename": "zeronlg/models/Transformer.py",
"retrieved_chunk": " trans_features = {'input_ids': features['input_ids'], 'attention_mask': features['attention_mask']}\n if 'token_type_ids' in features:\n trans_features['token_type_ids'] = features['token_type_ids'... | get_word_embedding_dimension(), 'mean') |
{
"list": [
{
"filename": "zeronlg/datasets/PretrainDataset.py",
"retrieved_chunk": " count += 1\n if max_sentences is not None and max_sentences > 0 and count >= max_sentences:\n break\n # show statistics and an example\n logger.info(f\"T... | import os
import torch
import json
import time
import shutil
import logging
import datetime
import random
import numpy as np
import transformers
import stat
import tempfile
import torch
import torch.backends.cudnn as cudnn
from torch import nn
from torch.optim import Optimizer
from torch.utils.data import DataLoader
... |
self.logger.info(info)
time_string = 'Train epoch time: ' + str(datetime.timedelta(seconds=int(time.time() - start_time)))
self.logger.info(time_string)
self._eval_during_training(evaluator, output_path, save_best_model, epoch, -1, callback)
if checkpoint_p... | {
"context_start_lineno": 0,
"file": "zeronlg/Framework.py",
"groundtruth_start_lineno": 514,
"repository": "yangbang18-ZeroNLG-bbd3f33",
"right_context_start_lineno": 515,
"task_id": "project_cc_python/2734"
} | {
"list": [
{
"filename": "train.py",
"retrieved_chunk": " weight_decay=args.weight_decay,\n output_path=output_path,\n checkpoint_path=output_path,\n checkpoint_save_steps=None, # save checkpoints every epoch, rather than spcific number of steps\n log_every=args.log... | global_avg()}" |
{
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": "import json\nimport sbi_web_api_py\nfrom typing import Tuple, Optional\nfrom sbi_web_api_py import raw_api, Job\nfrom sbi_web_api_py.type_hinting import JsonList, JsonObject\nfrom lcabyg_web_api_py import NewJob\nfrom lcabyg_... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
def api_get_jobs(self) -> IdList:
res = self._smart_call(raw_api.get_jobs)
return res
def api_get_job(self, job_id: str) -> Job:
res = self._smart_call(raw_api.get_job_by_id, job_id=job_id)
return Job.from_json(res)
def api_get_job_input(self, job_id: str) -> bytes:
... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 65,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 66,
"task_id": "project_cc_python/2793"
} | {
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": " def api_get_job_input(self, job_id: str) -> JsonList:\n data = super().api_get_job_input(job_id)\n return json.loads(data)\n def api_get_job_output(self, job_id: str) -> Optional[JsonObject]:\n dat... | from_json(res) |
{
"list": [
{
"filename": "zeronlg/evaluation/TranslateEvaluator.py",
"retrieved_chunk": " if output_path:\n self.log(f'Save translation results to {result_file}')\n json.dump(results, open(result_file, 'w'))\n if not no_score:\n scores = translate_eval(g... | import os
import json
import torch
import logging
from tqdm import tqdm
from torch.utils.data import DataLoader
from sentence_transformers import LoggingHandler
from typing import Dict, Any, Union
from .. import Framework, ZeroNLG
from ..datasets import CaptionDataset
from ..utils import coco_caption_eval
logging.ba... |
if output_path:
self.log(f'Save scores to {scores_file}')
json.dump(coco_test.eval, open(scores_file, 'w'))
for k, v in coco_test.eval.items():
self.log(f'[{prefix}] {k} {v}')
score = coco_test.eval[self.monitor]
return ... | {
"context_start_lineno": 0,
"file": "zeronlg/evaluation/CaptionEvaluator.py",
"groundtruth_start_lineno": 112,
"repository": "yangbang18-ZeroNLG-bbd3f33",
"right_context_start_lineno": 113,
"task_id": "project_cc_python/2735"
} | {
"list": [
{
"filename": "zeronlg/evaluation/TranslateEvaluator.py",
"retrieved_chunk": " score = scores[self.monitor]\n return score",
"score": 117.18138450663864
},
{
"filename": "zeronlg/evaluation/RetrievalEvaluator.py",
"retrieved_chunk": " ... | evalImgs, open(detailed_scores_file, 'w')) |
{
"list": [
{
"filename": "sbi_web_api_py/raw_api.py",
"retrieved_chunk": "import sys\nfrom uuid import UUID\nimport urllib.parse\nfrom typing import Optional, Dict, Tuple, Any\nimport requests\nfrom sbi_web_api_py.type_hinting import JsonObject\nclass AuthTokenExpired(Exception):\n def __init__(se... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
assert self._smart_call(raw_api.ping_secure) == 'pong secure'
def api_get_account_info(self) -> JsonObject:
return self._smart_call(raw_api.get_account)
def api_submit_job(self, job: NewJob) -> Job:
res = self._smart_call(raw_api.post_job, payload=job.to_dict())
return Job.fro... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 57,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 58,
"task_id": "project_cc_python/2789"
} | {
"list": [
{
"filename": "sbi_web_api_py/raw_api.py",
"retrieved_chunk": "def get(url: str,\n headers: Optional[Dict] = None,\n auth_token: Optional[UUID] = None) -> Any:\n if auth_token:\n if not headers:\n headers = dict()\n headers['Authorization'] = f'Bea... | ping(self._api_base_url) == 'pong' |
{
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": "import json\nimport sbi_web_api_py\nfrom typing import Tuple, Optional\nfrom sbi_web_api_py import raw_api, Job\nfrom sbi_web_api_py.type_hinting import JsonList, JsonObject\nfrom lcabyg_web_api_py import NewJob\nfrom lcabyg_... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
return Job.from_json(res)
def api_get_job_input(self, job_id: str) -> bytes:
res = self._smart_call(raw_api.get_job_input_by_id, job_id=job_id)
return unpack_bytes(res)
def api_get_job_output(self, job_id: str) -> bytes:
res = self._smart_call(raw_api.get_job_output_by_id, job... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 72,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 73,
"task_id": "project_cc_python/2795"
} | {
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": " def api_get_job_input(self, job_id: str) -> JsonList:\n data = super().api_get_job_input(job_id)\n return json.loads(data)\n def api_get_job_output(self, job_id: str) -> Optional[JsonObject]:\n dat... | get_job_by_id, job_id=job_id) |
{
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": "import json\nimport sbi_web_api_py\nfrom typing import Tuple, Optional\nfrom sbi_web_api_py import raw_api, Job\nfrom sbi_web_api_py.type_hinting import JsonList, JsonObject\nfrom lcabyg_web_api_py import NewJob\nfrom lcabyg_... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
def api_get_account_info(self) -> JsonObject:
return self._smart_call(raw_api.get_account)
def api_submit_job(self, job: NewJob) -> Job:
res = self._smart_call(raw_api.post_job, payload=job.to_dict())
return Job.from_json(res)
def api_get_jobs(self) -> IdList:
res = self.... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 58,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 59,
"task_id": "project_cc_python/2790"
} | {
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": " def api_get_job_input(self, job_id: str) -> JsonList:\n data = super().api_get_job_input(job_id)\n return json.loads(data)\n def api_get_job_output(self, job_id: str) -> Optional[JsonObject]:\n dat... | ping_secure) == 'pong secure' |
{
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": "import json\nimport sbi_web_api_py\nfrom typing import Tuple, Optional\nfrom sbi_web_api_py import raw_api, Job\nfrom sbi_web_api_py.type_hinting import JsonList, JsonObject\nfrom lcabyg_web_api_py import NewJob\nfrom lcabyg_... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
return Job.from_json(res)
def api_get_jobs(self) -> IdList:
res = self._smart_call(raw_api.get_jobs)
return res
def api_get_job(self, job_id: str) -> Job:
res = self._smart_call(raw_api.get_job_by_id, job_id=job_id)
return Job.from_json(res)
def api_get_job_input(... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 64,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 65,
"task_id": "project_cc_python/2792"
} | {
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": " def api_get_job_input(self, job_id: str) -> JsonList:\n data = super().api_get_job_input(job_id)\n return json.loads(data)\n def api_get_job_output(self, job_id: str) -> Optional[JsonObject]:\n dat... | post_job, payload=job.to_dict()) |
{
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": " def api_get_job_input(self, job_id: str) -> JsonList:\n data = super().api_get_job_input(job_id)\n return json.loads(data)\n def api_get_job_output(self, job_id: str) -> Optional[JsonObject]:\n dat... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
return unpack_bytes(res)
def api_get_job_output(self, job_id: str) -> bytes:
res = self._smart_call(raw_api.get_job_output_by_id, job_id=job_id)
return unpack_bytes(res)
def api_mark_job_as_finished(self, job_id: str):
self._smart_call(raw_api.mark_job_as_finished, job_id=job_... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 76,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 77,
"task_id": "project_cc_python/2796"
} | {
"list": [
{
"filename": "lcabyg_web_api_py/client.py",
"retrieved_chunk": " return super().submit_job(project, pool_interval=pool_interval, auto_mark_as_finished=auto_mark_as_finished)",
"score": 50.100936691186625
},
{
"filename": "lcabyg_web_api_py/client.py",
"ret... | get_job_input_by_id, job_id=job_id) |
{
"list": [
{
"filename": "sbi_web_api_py/job_status.py",
"retrieved_chunk": " return False\n else:\n return True\n def failed(self) -> bool:\n if self == JobStatus.FAILED or self == JobStatus.ABANDONED:\n return True\n else:\n return... | import json
import logging
import time
from typing import List, Tuple
from sbi_web_api_py.type_hinting import JsonList, JsonObject, IdList
from sbi_web_api_py.new_job import NewJob
from sbi_web_api_py.job import Job
from sbi_web_api_py.utils import unpack_bytes
from sbi_web_api_py import raw_api
class JobFailed(Excep... |
def _smart_call(self, api_function, *args, **kwargs):
# Inject the auth token
if 'auth_token' not in kwargs:
kwargs['auth_token'] = self._token
else:
logging.warning('Auth token for smart_call overridden!')
# Inject base url
if 'api_root' not in kwa... | {
"context_start_lineno": 0,
"file": "sbi_web_api_py/client.py",
"groundtruth_start_lineno": 34,
"repository": "build-aau-lcabyg_web_api_doc-b001c5d",
"right_context_start_lineno": 35,
"task_id": "project_cc_python/2787"
} | {
"list": [
{
"filename": "sbi_web_api_py/job_status.py",
"retrieved_chunk": " return False\n else:\n return True\n def failed(self) -> bool:\n if self == JobStatus.FAILED or self == JobStatus.ABANDONED:\n return True\n else:\n return... | login_via_body(self._api_base_url, self._username, self._password) |
{
"list": [
{
"filename": "src/routes/transform_post.py",
"retrieved_chunk": "router = APIRouter(prefix='/transformations', tags=[\"transformations\"])\n@router.patch(\"/{post_id}\", response_model=PostResponse, status_code=status.HTTP_200_OK)\nasync def transform_metod(post_id: int, body: TransformBo... | import base64
import cloudinary
import pyqrcode
import io
from sqlalchemy.orm import Session
from src.database.models import Post, User
from src.conf.config import init_cloudinary
from src.tramsform_schemas import TransformBodyModel
async def transform_metod(post_id: int, body: TransformBodyModel, user: User, db: S... |
if post:
transformation = []
if body.circle.use_filter and body.circle.height and body.circle.width:
trans_list = [{'gravity': "face", 'height': f"{body.circle.height}", 'width': f"{body.circle.width}", 'crop': "thumb"},
{'radius': "max"}]
[transformatio... | {
"context_start_lineno": 0,
"file": "src/repository/transform_post.py",
"groundtruth_start_lineno": 26,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 27,
"task_id": "project_cc_python/2799"
} | {
"list": [
{
"filename": "tests/transformations/test_repository_transform_post.py",
"retrieved_chunk": " body = TransformBodyModel(**body)\n response = await transform_metod(post.id, body, new_user, session)\n assert post.image_url != response.transform_url \n@pytest.mark.asyncio\nasync def ... | user_id == user.id, Post.id == post_id).first() |
{
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": "async def delete_comment(comment_id: int, db: Session = Depends(get_db),\n current_user: User = Depends(auth_service.get_current_user)):\n \"\"\"\n The delete_comment function deletes a comment from t... | from typing import List
from sqlalchemy.orm import Session
from sqlalchemy import and_, func
from src.database.models import User, Comment, UserRoleEnum
from src.schemas import CommentBase
async def create_comment(post_id: int, body: CommentBase, db: Session, user: User) -> Comment:
"""
The create_comment ... |
comment.text = body.text
comment.updated_at = func.now()
comment.update_status = True
db.commit()
return comment
async def delete_comment(comment_id: int, db: Session, user: User) -> None:
"""
The delete_comment function deletes a comment from the database... | {
"context_start_lineno": 0,
"file": "src/repository/comments.py",
"groundtruth_start_lineno": 48,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 49,
"task_id": "project_cc_python/2813"
} | {
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " return new_comment\n@router.put(\"/edit/{comment_id}\", response_model=CommentUpdate, dependencies=[Depends(allowed_update_comments)])\nasync def edit_comment(comment_id: int, body: CommentBase, db: Session = Depends(get_db),\... | admin, UserRoleEnum.moder] or comment.user_id == user.id: |
{
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " user_id (int): The id of the user whose comments are being retrieved.\n post_id (int): The id of the post whose comments are being retrieved.\n Returns:\n A list containing all comment obje... | from typing import List
from sqlalchemy.orm import Session
from sqlalchemy import and_, func
from src.database.models import User, Comment, UserRoleEnum
from src.schemas import CommentBase
async def create_comment(post_id: int, body: CommentBase, db: Session, user: User) -> Comment:
"""
The create_comment ... | {
"context_start_lineno": 0,
"file": "src/repository/comments.py",
"groundtruth_start_lineno": 120,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 121,
"task_id": "project_cc_python/2816"
} | {
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " comments = await repository_comments.show_user_post_comments(user_id, post_id, db)\n if comments is None:\n raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.COMM_NOT_FOUND)\n return commen... | post_id == post_id, Comment.user_id == user_id)).all() | |
{
"list": [
{
"filename": "src/routes/ratings.py",
"retrieved_chunk": " The edit_rate function allows a user to edit their rating of a community.\n The function takes in the rate_id, new_rate, db and current_user as parameters.\n It then calls the edit_rate function from repository/ra... | from typing import Type
from fastapi import HTTPException
from sqlalchemy.orm import Session
from sqlalchemy import and_
from starlette import status
from src.database.models import Rating, User, Post, UserRoleEnum
from src.conf import messages as message
async def create_rate(post_id: int, rate: int, db: Session, ... |
if rate:
rate.rate = new_rate
db.commit()
return rate
async def delete_rate(rate_id: int, db: Session, user: User) -> Type[Rating]:
"""
The delete_rate function deletes a rating from the database.
Args:
rate_id (int): The id of the rating to be deleted.... | {
"context_start_lineno": 0,
"file": "src/repository/ratings.py",
"groundtruth_start_lineno": 57,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 58,
"task_id": "project_cc_python/2824"
} | {
"list": [
{
"filename": "src/routes/ratings.py",
"retrieved_chunk": " edited_rate = await repository_ratings.edit_rate(rate_id, new_rate, db, current_user)\n if edited_rate is None:\n raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.COMM_NOT_FOUND)\n return e... | admin, UserRoleEnum.moder] or rate.user_id == user.id: |
{
"list": [
{
"filename": "src/routes/ratings.py",
"retrieved_chunk": " The edit_rate function allows a user to edit their rating of a community.\n The function takes in the rate_id, new_rate, db and current_user as parameters.\n It then calls the edit_rate function from repository/ra... | from typing import Type
from fastapi import HTTPException
from sqlalchemy.orm import Session
from sqlalchemy import and_
from starlette import status
from src.database.models import Rating, User, Post, UserRoleEnum
from src.conf import messages as message
async def create_rate(post_id: int, rate: int, db: Session, ... |
if rate:
rate.rate = new_rate
db.commit()
return rate
async def delete_rate(rate_id: int, db: Session, user: User) -> Type[Rating]:
"""
The delete_rate function deletes a rating from the database.
Args:
rate_id (int): The id of the rating to be deleted.... | {
"context_start_lineno": 0,
"file": "src/repository/ratings.py",
"groundtruth_start_lineno": 57,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 58,
"task_id": "project_cc_python/2825"
} | {
"list": [
{
"filename": "src/routes/ratings.py",
"retrieved_chunk": " edited_rate = await repository_ratings.edit_rate(rate_id, new_rate, db, current_user)\n if edited_rate is None:\n raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.COMM_NOT_FOUND)\n return e... | moder] or rate.user_id == user.id: |
{
"list": [
{
"filename": "src/repository/hashtags.py",
"retrieved_chunk": " db.refresh(tag)\n return tag\nasync def get_my_tags(skip: int, limit: int, user: User, db: Session) -> List[Hashtag]:\n \"\"\"\n The get_my_tags function returns a list of Hashtag objects that are associated w... | from typing import List
from fastapi import APIRouter, HTTPException, Depends, status
from sqlalchemy.orm import Session
from src.conf.messages import NOT_FOUND
from src.database.connect_db import get_db
from src.schemas import HashtagBase, HashtagResponse
from src.repository import hashtags as repository_tags
from s... |
return tags
@router.get("/all/", response_model=List[HashtagResponse], dependencies=[Depends(allowed_get_all_hashtags)])
async def read_all_tags(skip: int = 0, limit: int = 100, db: Session = Depends(get_db),
current_user: User = Depends(auth_service.get_current_user)):
"""
The rea... | {
"context_start_lineno": 0,
"file": "src/routes/hashtags.py",
"groundtruth_start_lineno": 55,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 56,
"task_id": "project_cc_python/2833"
} | {
"list": [
{
"filename": "src/repository/hashtags.py",
"retrieved_chunk": " :return: A list of hashtags that belong to the user\n \"\"\"\n return db.query(Hashtag).filter(Hashtag.user_id == user.id).offset(skip).limit(limit).all()\nasync def get_all_tags(skip: int, limit: int, db: Session) -... | get_my_tags(skip, limit, current_user, db) |
{
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " :param db: Session: Get the database session\n :return: A dictionary with a message\n \"\"\"\n user = await repository_users.get_user_by_email(body.email, db)\n if not user:\n raise HTTPException(status_code=st... | from fastapi import APIRouter, HTTPException, Depends, status, Security, BackgroundTasks, Request
from fastapi.security import OAuth2PasswordRequestForm, HTTPAuthorizationCredentials, HTTPBearer
from sqlalchemy.orm import Session
from src.database.models import User
from src.services.email import send_email
from src.d... |
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail=INVALID_PASSWORD)
# Generate JWT
access_token = await auth_service.create_access_token(data={"sub": user.email}, expires_delta=7200)
refresh_token = await auth_service.create_refresh_token(data={"sub": user.email})
await repos... | {
"context_start_lineno": 0,
"file": "src/routes/auth.py",
"groundtruth_start_lineno": 59,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 60,
"task_id": "project_cc_python/2841"
} | {
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail=USER_ALREADY_NOT_ACTIVE)\n@router.patch(\"/make_role/{email}/\", dependencies=[Depends(allowed_change_user_role)])\nasync def make_role_by_email(body: RequestRo... | verify_password(body.password, user.password): |
{
"list": [
{
"filename": "src/repository/hashtags.py",
"retrieved_chunk": " body (HashtagBase): The new values for the updated tag.\n db (Session): A connection to our database session, used for querying and committing changes.\n :param tag_id: int: Identify the tag to be upd... | from typing import List
from fastapi import APIRouter, HTTPException, Depends, status
from sqlalchemy.orm import Session
from src.conf.messages import NOT_FOUND
from src.database.connect_db import get_db
from src.schemas import HashtagBase, HashtagResponse
from src.repository import hashtags as repository_tags
from s... |
@router.get("/my/", response_model=List[HashtagResponse])
async def read_my_tags(skip: int = 0, limit: int = 100, db: Session = Depends(get_db),
current_user: User = Depends(auth_service.get_current_user)):
"""
The read_my_tags function returns a list of tags that the current user has ... | {
"context_start_lineno": 0,
"file": "src/routes/hashtags.py",
"groundtruth_start_lineno": 39,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 40,
"task_id": "project_cc_python/2832"
} | {
"list": [
{
"filename": "src/repository/hashtags.py",
"retrieved_chunk": " db.commit()\n return tag\nasync def remove_tag(tag_id: int, db: Session) -> Hashtag | None:\n \"\"\"\n The remove_tag function removes a tag from the database.\n :param tag_id: int: Specify the id of the ta... | create_tag(body, current_user, db) |
{
"list": [
{
"filename": "src/repository/posts.py",
"retrieved_chunk": " \"\"\"\n searched_user = db.query(User).filter(func.lower(User.username).like(f'%{user_name.lower()}%')).first()\n if searched_user:\n return db.query(Post).filter(Post.user_id == searched_user.id).all()\nasync d... | from datetime import datetime
from typing import List
import cloudinary
import cloudinary.uploader
from sqlalchemy import func
from sqlalchemy.orm import Session
from src.conf.config import init_cloudinary
from src.conf.messages import USER_NOT_ACTIVE
from src.database.models import User, UserRoleEnum, Comment, Rati... |
async def get_user_profile(username: str, db: Session) -> User:
"""
The get_user_profile function returns a UserProfileModel object containing the user's username, email,
avatar, created_at date and time (in UTC), is_active status (True or False),
post count, comment count and rates count.
:... | {
"context_start_lineno": 0,
"file": "src/repository/users.py",
"groundtruth_start_lineno": 77,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 78,
"task_id": "project_cc_python/2805"
} | {
"list": [
{
"filename": "src/repository/posts.py",
"retrieved_chunk": " :return: A list of post objects\n \"\"\"\n return db.query(Post).filter(Post.user_id == user_id).all()\nasync def get_posts_by_username(user_name: str, db: Session) -> List[Post]: \n \"\"\"\n The get_posts_by_user... | username).like(f'%{username.lower()}%')).all() |
{
"list": [
{
"filename": "src/repository/transform_post.py",
"retrieved_chunk": " The transform_metod function takes in a post_id, body, user and db as parameters.\n It then queries the database for the post with that id and if it exists it creates an empty list called transformation.\n If a... | from typing import List
from fastapi import APIRouter, HTTPException, Depends, status
from sqlalchemy.orm import Session
from src.conf.messages import NOT_FOUND
from src.database.connect_db import get_db
from src.database.models import User
from src.schemas import PostResponse
from src.services.auth import auth_servi... |
if post is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=NOT_FOUND)
return post
@router.post("/qr/{post_id}", status_code=status.HTTP_200_OK)
async def show_qr(post_id: int, db: Session = Depends(get_db),
current_user: User = Depends(auth_service.get_current_user... | {
"context_start_lineno": 0,
"file": "src/routes/transform_post.py",
"groundtruth_start_lineno": 29,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 30,
"task_id": "project_cc_python/2828"
} | {
"list": [
{
"filename": "src/repository/transform_post.py",
"retrieved_chunk": " \"\"\"\n post= db.query(Post).filter(Post.user_id == user.id, Post.id == post_id).first()\n if post:\n transformation = []\n if body.circle.use_filter and body.circle.height and body.circle.width:... | transform_metod(post_id, body, current_user, db) |
{
"list": [
{
"filename": "src/services/email.py",
"retrieved_chunk": " \"\"\"\n The send_email function sends an email to the user with a link to confirm their email address.\n The function takes in three arguments:\n -email: the user's email address, which is used as a unique... | from fastapi import APIRouter, HTTPException, Depends, status, Security, BackgroundTasks, Request
from fastapi.security import OAuth2PasswordRequestForm, HTTPAuthorizationCredentials, HTTPBearer
from sqlalchemy.orm import Session
from src.database.models import User
from src.services.email import send_email
from src.d... |
user = await repository_users.get_user_by_email(email, db)
if user is None:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=VERIFICATION_ERROR)
if user.is_verify:
return {"message": EMAIL_ALREADY_CONFIRMED}
await repository_users.confirmed_email(email, db)
return... | {
"context_start_lineno": 0,
"file": "src/routes/auth.py",
"groundtruth_start_lineno": 116,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 117,
"task_id": "project_cc_python/2848"
} | {
"list": [
{
"filename": "src/services/email.py",
"retrieved_chunk": " :param host: str: Pass the hostname of your application to the template\n :return: A coroutine object\n \"\"\"\n try:\n token_verification = auth_service.create_email_token({\"sub\": email})\n message = M... | get_email_from_token(token) |
{
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " :param db: Session: Access the database\n :return: A dictionary with a message key\n \"\"\"\n user = await repository_users.get_user_by_email(body.email, db)\n if not user:\n raise HTTPException(status_code=sta... | from fastapi import APIRouter, HTTPException, Depends, status, Security, BackgroundTasks, Request
from fastapi.security import OAuth2PasswordRequestForm, HTTPAuthorizationCredentials, HTTPBearer
from sqlalchemy.orm import Session
from src.database.models import User
from src.services.email import send_email
from src.d... |
new_user = await repository_users.create_user(body, db)
background_tasks.add_task(send_email, new_user.email, new_user.username, request.base_url)
return {"user": new_user, "detail": SUCCESS_CREATE_USER}
@router.post("/login", response_model=TokenModel)
async def login(body: OAuth2PasswordRequestForm = D... | {
"context_start_lineno": 0,
"file": "src/routes/auth.py",
"groundtruth_start_lineno": 35,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 36,
"task_id": "project_cc_python/2839"
} | {
"list": [
{
"filename": "src/routes/posts.py",
"retrieved_chunk": " return post\n@router.delete(\"/{post_id}\", response_model=PostResponse)\nasync def remove_post(post_id: int, db: Session = Depends(get_db),\n current_user: User = Depends(auth_service.get_current_user)):\n \"\"\"\n... | get_password_hash(body.password) |
{
"list": [
{
"filename": "src/repository/hashtags.py",
"retrieved_chunk": " db.refresh(tag)\n return tag\nasync def get_my_tags(skip: int, limit: int, user: User, db: Session) -> List[Hashtag]:\n \"\"\"\n The get_my_tags function returns a list of Hashtag objects that are associated w... | from typing import List
from fastapi import APIRouter, HTTPException, Depends, status
from sqlalchemy.orm import Session
from src.conf.messages import NOT_FOUND
from src.database.connect_db import get_db
from src.schemas import HashtagBase, HashtagResponse
from src.repository import hashtags as repository_tags
from s... |
return tags
@router.get("/by_id/{tag_id}", response_model=HashtagResponse)
async def read_tag_by_id(tag_id: int, db: Session = Depends(get_db),
current_user: User = Depends(auth_service.get_current_user)):
"""
The read_tag_by_id function returns a single tag by its id.
The function ta... | {
"context_start_lineno": 0,
"file": "src/routes/hashtags.py",
"groundtruth_start_lineno": 73,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 74,
"task_id": "project_cc_python/2834"
} | {
"list": [
{
"filename": "src/repository/hashtags.py",
"retrieved_chunk": " :return: A list of hashtags that belong to the user\n \"\"\"\n return db.query(Hashtag).filter(Hashtag.user_id == user.id).offset(skip).limit(limit).all()\nasync def get_all_tags(skip: int, limit: int, db: Session) -... | get_all_tags(skip, limit, db) |
{
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": "async def delete_comment(comment_id: int, db: Session = Depends(get_db),\n current_user: User = Depends(auth_service.get_current_user)):\n \"\"\"\n The delete_comment function deletes a comment from t... | from typing import List
from sqlalchemy.orm import Session
from sqlalchemy import and_, func
from src.database.models import User, Comment, UserRoleEnum
from src.schemas import CommentBase
async def create_comment(post_id: int, body: CommentBase, db: Session, user: User) -> Comment:
"""
The create_comment ... |
comment.text = body.text
comment.updated_at = func.now()
comment.update_status = True
db.commit()
return comment
async def delete_comment(comment_id: int, db: Session, user: User) -> None:
"""
The delete_comment function deletes a comment from the database... | {
"context_start_lineno": 0,
"file": "src/repository/comments.py",
"groundtruth_start_lineno": 48,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 49,
"task_id": "project_cc_python/2814"
} | {
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " return new_comment\n@router.put(\"/edit/{comment_id}\", response_model=CommentUpdate, dependencies=[Depends(allowed_update_comments)])\nasync def edit_comment(comment_id: int, body: CommentBase, db: Session = Depends(get_db),\... | moder] or comment.user_id == user.id: |
{
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " :param db: Session: Get the database session\n :return: A dictionary with a message\n \"\"\"\n user = await repository_users.get_user_by_email(body.email, db)\n if not user:\n raise HTTPException(status_code=st... | from fastapi import APIRouter, HTTPException, Depends, status, Security, BackgroundTasks, Request
from fastapi.security import OAuth2PasswordRequestForm, HTTPAuthorizationCredentials, HTTPBearer
from sqlalchemy.orm import Session
from src.database.models import User
from src.services.email import send_email
from src.d... |
return {"message": EMAIL_CONFIRMED}
@router.post('/request_email')
async def request_email(body: RequestEmail, background_tasks: BackgroundTasks, request: Request,
db: Session = Depends(get_db)):
"""
The request_email function is used to send an email to the user with a link that ... | {
"context_start_lineno": 0,
"file": "src/routes/auth.py",
"groundtruth_start_lineno": 122,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 123,
"task_id": "project_cc_python/2849"
} | {
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail=USER_ALREADY_NOT_ACTIVE)\n@router.patch(\"/make_role/{email}/\", dependencies=[Depends(allowed_change_user_role)])\nasync def make_role_by_email(body: RequestRo... | confirmed_email(email, db) |
{
"list": [
{
"filename": "src/repository/comments.py",
"retrieved_chunk": " :param user: User: Check if the user is authorized to see the comment\n :return: The comment with the given id, if it exists\n \"\"\"\n return db.query(Comment).filter(and_(Comment.id == comment_id, Comment.user_i... | from fastapi import APIRouter, HTTPException, Depends, status, Request
from sqlalchemy.orm import Session
from typing import List
from src.database.models import User
from src.database.connect_db import get_db
from src.schemas import CommentBase, CommentUpdate, CommentModel
from src.repository import comments as repos... |
if comments is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.COMM_NOT_FOUND)
return comments
@router.get("/post_by_author/{user_id}/{post_id}", response_model=List[CommentModel],
dependencies=[Depends(allowed_get_comments)])
async def by_user_post_comment... | {
"context_start_lineno": 0,
"file": "src/routes/comments.py",
"groundtruth_start_lineno": 118,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 119,
"task_id": "project_cc_python/2859"
} | {
"list": [
{
"filename": "src/repository/comments.py",
"retrieved_chunk": " :return: A list of comments\n \"\"\"\n return db.query(Comment).filter(Comment.user_id == user_id).all()\nasync def show_user_post_comments(user_id: int, post_id: int, db: Session) -> List[Comment] | None:\n \"\"\... | show_user_comments(user_id, db) |
{
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " :param db: Session: Get the database session\n :return: A dictionary with a message\n \"\"\"\n user = await repository_users.get_user_by_email(body.email, db)\n if not user:\n raise HTTPException(status_code=st... | from fastapi import APIRouter, HTTPException, Depends, status, Security, BackgroundTasks, Request
from fastapi.security import OAuth2PasswordRequestForm, HTTPAuthorizationCredentials, HTTPBearer
from sqlalchemy.orm import Session
from src.database.models import User
from src.services.email import send_email
from src.d... |
refresh_token = await auth_service.create_refresh_token(data={"sub": user.email})
await repository_users.update_token(user, refresh_token, db)
return {"access_token": access_token, "refresh_token": refresh_token, "token_type": "bearer"}
@router.post("/logout")
async def logout(credentials: HTTPAuthorizat... | {
"context_start_lineno": 0,
"file": "src/routes/auth.py",
"groundtruth_start_lineno": 62,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 63,
"task_id": "project_cc_python/2842"
} | {
"list": [
{
"filename": "src/routes/users.py",
"retrieved_chunk": " raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail=USER_ALREADY_NOT_ACTIVE)\n@router.patch(\"/make_role/{email}/\", dependencies=[Depends(allowed_change_user_role)])\nasync def make_role_by_email(body: RequestRo... | create_access_token(data={"sub": user.email}, expires_delta=7200) |
{
"list": [
{
"filename": "src/repository/comments.py",
"retrieved_chunk": " return comment\nasync def show_single_comment(comment_id: int, db: Session, user: User) -> Comment | None:\n \"\"\"\n The show_single_comment function returns a single comment from the database.\n Args:\n ... | from fastapi import APIRouter, HTTPException, Depends, status, Request
from sqlalchemy.orm import Session
from typing import List
from src.database.models import User
from src.database.connect_db import get_db
from src.schemas import CommentBase, CommentUpdate, CommentModel
from src.repository import comments as repos... |
if comment is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.COMM_NOT_FOUND)
return comment
@router.get("/by_author/{user_id}", response_model=List[CommentModel], dependencies=[Depends(allowed_get_comments)])
async def by_user_comments(user_id: int, db: Session = Depe... | {
"context_start_lineno": 0,
"file": "src/routes/comments.py",
"groundtruth_start_lineno": 95,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 96,
"task_id": "project_cc_python/2858"
} | {
"list": [
{
"filename": "src/repository/comments.py",
"retrieved_chunk": " :param user: User: Check if the user is authorized to see the comment\n :return: The comment with the given id, if it exists\n \"\"\"\n return db.query(Comment).filter(and_(Comment.id == comment_id, Comment.user_i... | show_single_comment(comment_id, db, current_user) |
{
"list": [
{
"filename": "tests/posts/test_repository_posts.py",
"retrieved_chunk": "@pytest.mark.asyncio\nasync def test_get_posts_by_username(current_user, session):\n \"\"\"\n The test_get_posts_by_username function tests the get_posts_by_username function in the repository.py file.\n It ... | import pytest
from src.database.models import User
from src.repository import users as repository_users
from src.schemas import UserModel
from src.database.models import UserRoleEnum
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.... |
assert isinstance(response, list)
assert response[0].username == "artur4ik"
assert response[0].email == "artur4ik@example.com"
@pytest.mark.asyncio
async def test_get_user_profile(new_user, session):
"""
The test_get_user_profile function tests the get_user_profile function in the reposit... | {
"context_start_lineno": 0,
"file": "tests/users/test_repository_users.py",
"groundtruth_start_lineno": 98,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 99,
"task_id": "project_cc_python/2882"
} | {
"list": [
{
"filename": "tests/posts/test_repository_posts.py",
"retrieved_chunk": " assert isinstance(response, list)\n assert response[0].title == \"test_post\"\n assert response[0].descr == \"test_post\"\n@pytest.mark.asyncio\nasync def test_get_posts_with_hashtag(session):\n \"\"\"\n... | get_users_with_username("artur", session) |
{
"list": [
{
"filename": "tests/rating/test_repository_ratings.py",
"retrieved_chunk": " assert response.user_id == 1\n assert response.post_id == 1\n@pytest.mark.asyncio\nasync def test_delete_rate(new_user, session):\n \"\"\"\n The test_delete_rate function tests the delete_rate functio... | import pytest
from src.database.models import User
from src.repository import users as repository_users
from src.schemas import UserModel
from src.database.models import UserRoleEnum
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.... |
assert response.username == "artur4ik"
assert response.email == "artur4ik@example.com"
@pytest.mark.asyncio
async def test_get_users(new_user, second_user, session):
"""
The test_get_users function tests the get_users function in the repository_users module.
It creates two users, and then calls g... | {
"context_start_lineno": 0,
"file": "tests/users/test_repository_users.py",
"groundtruth_start_lineno": 65,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 66,
"task_id": "project_cc_python/2880"
} | {
"list": [
{
"filename": "tests/rating/test_repository_ratings.py",
"retrieved_chunk": " :param session: Pass the database session to the function\n :return: A response object\n \"\"\"\n response = await repository_ratings.delete_rate(1, session, new_user)\n assert response.rate == 5\n... | get_me(new_user, session) |
{
"list": [
{
"filename": "src/routes/hashtags.py",
"retrieved_chunk": " :param current_user: User: Get the user that is currently logged in\n :return: A list of tag objects\n \"\"\"\n tags = await repository_tags.get_my_tags(skip, limit, current_user, db)\n return tags\n@router.get(\"/... | from typing import List
from fastapi import APIRouter, HTTPException, Depends, status, Request, Path
from sqlalchemy.orm import Session
from src.database.connect_db import get_db
from src.schemas import RatingModel, PostResponse
from src.repository import ratings as repository_ratings
from src.services.auth import au... |
if comments is None:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.NO_RATING)
return comments
@router.get("/all_my", response_model=List[RatingModel], dependencies=[Depends(allowed_commented_by_user)])
async def all_my_rates(db: Session = Depends(get_db), current_user: Use... | {
"context_start_lineno": 0,
"file": "src/routes/ratings.py",
"groundtruth_start_lineno": 98,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 99,
"task_id": "project_cc_python/2871"
} | {
"list": [
{
"filename": "src/routes/hashtags.py",
"retrieved_chunk": " The function takes two optional parameters: skip and limit, which are used to paginate the results.\n If no parameters are provided, then it will return up to 100 tags starting from the first tag.\n :param skip: ... | show_ratings(db, current_user) |
{
"list": [
{
"filename": "tests/posts/test_repository_posts.py",
"retrieved_chunk": " assert response.title == \"test_post\"\n assert response.descr == \"test_post\"\n@pytest.mark.asyncio\nasync def test_get_posts_by_title(current_user, session):\n \"\"\"\n The test_get_posts_by_title fun... | import pytest
from src.database.models import User
from src.repository import users as repository_users
from src.schemas import UserModel
from src.database.models import UserRoleEnum
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.... |
assert response.username == "second_user"
assert response.email == "second_user@example.com"
@pytest.mark.asyncio
async def test_create_user(user, session):
"""
The test_create_user function tests the create_user function in repository_users.py
by creating a new user and checking if i... | {
"context_start_lineno": 0,
"file": "tests/users/test_repository_users.py",
"groundtruth_start_lineno": 164,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 165,
"task_id": "project_cc_python/2886"
} | {
"list": [
{
"filename": "tests/comments/test_repository_comments.py",
"retrieved_chunk": " assert isinstance(response, list)\n assert response[0].user_id == 1\n@pytest.mark.asyncio\nasync def test_show_user_post_comments(new_user, session):\n \"\"\"\n The test_show_user_post_comments fun... | get_user_by_email("second_user@example.com", session) |
{
"list": [
{
"filename": "src/repository/users.py",
"retrieved_chunk": " db.commit()\nasync def confirmed_email(email: str, db: Session) -> None:\n \"\"\"\n The confirmed_email function sets the confirmed field of a user to True.\n :param email: str: Get the email of the user that is tryi... | import pytest
from src.database.models import User
from src.repository import users as repository_users
from src.schemas import UserModel
from src.database.models import UserRoleEnum
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.... |
second_user = await repository_users.get_user_by_email("second_user@example.com", session)
assert second_user.is_verify == True
@pytest.mark.asyncio
async def test_ban_user(user, session):
"""
The test_ban_user function tests the ban_user function in repository_users.py
by checking if a user ... | {
"context_start_lineno": 0,
"file": "tests/users/test_repository_users.py",
"groundtruth_start_lineno": 200,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 201,
"task_id": "project_cc_python/2888"
} | {
"list": [
{
"filename": "tests/users/test_route_users.py",
"retrieved_chunk": " with patch.object(auth_service, 'redis_cache') as r_mock:\n r_mock.get.return_value = None\n current_user: User = session.query(User).filter(User.email == user.get('email')).first()\n new_user = U... | confirmed_email("second_user@example.com", session) |
{
"list": [
{
"filename": "tests/hashtags/test_repository_hashtags.py",
"retrieved_chunk": " The test_get_my_tags function tests the get_my_tags function in repository/tag.py\n It creates a new user, and then calls the get_my_tags function with skip=0, limit=100\n The response is chec... | import pytest
from src.database.models import User
from src.repository import users as repository_users
from src.schemas import UserModel
from src.database.models import UserRoleEnum
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.... |
assert isinstance(response, list)
assert len(response) == 2
@pytest.mark.asyncio
async def test_get_users_with_username(new_user, session):
"""
The test_get_users_with_username function tests the get_users_with_username function in the repository.py file.
It checks if it returns a list of users w... | {
"context_start_lineno": 0,
"file": "tests/users/test_repository_users.py",
"groundtruth_start_lineno": 82,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 83,
"task_id": "project_cc_python/2881"
} | {
"list": [
{
"filename": "tests/hashtags/test_repository_hashtags.py",
"retrieved_chunk": " assert isinstance(response, list)\n assert len(response) >= 1\n@pytest.mark.asyncio\nasync def test_get_all_tags(session):\n \"\"\"\n The test_get_all_tags function tests the get_all_tags function ... | get_users(0, 100, session) |
{
"list": [
{
"filename": "src/repository/users.py",
"retrieved_chunk": " user = await get_user_by_email(email, db)\n user.is_active = False\n db.commit()\nasync def make_user_role(email: str, role: UserRoleEnum, db: Session) -> None:\n \"\"\"\n The make_user_role function takes in an e... | import pytest
from src.database.models import User
from src.repository import users as repository_users
from src.schemas import UserModel
from src.database.models import UserRoleEnum
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.... |
second_user = await repository_users.get_user_by_email("second_user@example.com", session)
assert second_user.role == UserRoleEnum.moder
| {
"context_start_lineno": 0,
"file": "tests/users/test_repository_users.py",
"groundtruth_start_lineno": 230,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 231,
"task_id": "project_cc_python/2890"
} | {
"list": [
{
"filename": "tests/comments/test_repository_comments.py",
"retrieved_chunk": " \"\"\"\n response = await repository_comments.show_user_post_comments(1, 1, session)\n assert isinstance(response, list)\n assert response[0].user_id == 1",
"score": 55.80136420097926
},
... | make_user_role("second_user@example.com", "moder", session) |
{
"list": [
{
"filename": "tests/posts/test_route_posts.py",
"retrieved_chunk": " :param token: Authenticate the user\n :return: A response with a 201 status code and the data from the post\n \"\"\"\n with patch.object(auth_service, 'redis_cache') as r_mock:\n r_mock.get.return_valu... | from datetime import datetime
import pytest
import io
from fastapi import Request, UploadFile
from PIL import Image
from src.database.models import User, Post
import src.repository.posts as repository_posts
from src.schemas import PostUpdate
@pytest.fixture()
def current_user(user, session):
"""
The current... |
assert isinstance(response.image_url, str)
assert response.title == title
assert response.descr == descr
@pytest.mark.asyncio
async def test_get_all_posts(session):
"""
The test_get_all_posts function tests the get_all_posts function in the repository_posts module.
The test passes if:
... | {
"context_start_lineno": 0,
"file": "tests/posts/test_repository_posts.py",
"groundtruth_start_lineno": 99,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 100,
"task_id": "project_cc_python/2904"
} | {
"list": [
{
"filename": "tests/posts/test_route_posts.py",
"retrieved_chunk": " \"title\": \"test_post\",\n \"descr\": \"test_post\",\n \"hashtags\": [\"test_post\"]\n }\n response = client.post(\n \"/api/posts/new/\",\n header... | create_post(request, title, descr, hashtags, file, session, current_user) |
{
"list": [
{
"filename": "tests/posts/test_repository_posts.py",
"retrieved_chunk": "async def test_get_post_by_keyword(post, session):\n \"\"\"\n The test_searcher function tests the searcher function in repository_posts.py\n It creates a post with title and descr "test_post" ... | from datetime import datetime
import pytest
from src.database.models import User, Comment, Post
from src.schemas import CommentBase
from src.repository import comments as repository_comments
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as a... |
assert response.text == "new_comment"
@pytest.mark.asyncio
async def test_show_single_comment(comment, new_user, session):
"""
The test_show_single_comment function tests the show_single_comment function in repository_comments.py
by asserting that the response text is equal to "test_... | {
"context_start_lineno": 0,
"file": "tests/comments/test_repository_comments.py",
"groundtruth_start_lineno": 135,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 136,
"task_id": "project_cc_python/2899"
} | {
"list": [
{
"filename": "tests/posts/test_repository_posts.py",
"retrieved_chunk": " :return: A list of posts that have the title "test_post"\n \"\"\"\n post_title = \"test_post\"\n response = await repository_posts.get_posts_by_title(post_title, current_user, session)\n ass... | delete_comment(1, session, new_user) |
{
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " The function takes in an integer representing the id of the comment to be returned,\n and two optional parameters: db and current_user. If no db is provided, it will use \n get_db() to create a new connection... | from datetime import datetime
import pytest
from src.database.models import User, Comment, Post
from src.schemas import CommentBase
from src.repository import comments as repository_comments
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as a... |
assert response.text == "test_comment"
@pytest.mark.asyncio
async def test_show_user_comments(new_user, session):
"""
The test_show_user_comments function tests the show_user_comments function in repository_comments.py
It does this by creating a new user and then calling the show_user_com... | {
"context_start_lineno": 0,
"file": "tests/comments/test_repository_comments.py",
"groundtruth_start_lineno": 150,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 151,
"task_id": "project_cc_python/2900"
} | {
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " if comment is None:\n raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=message.COMM_NOT_FOUND)\n return comment\n@router.get(\"/by_author/{user_id}\", response_model=List[CommentModel], dependencies=... | show_single_comment(1, session, new_user) |
{
"list": [
{
"filename": "src/routes/comments.py",
"retrieved_chunk": " The create_comment function creates a new comment for the post with the given id.\n The body of the comment is passed in as JSON data, and must contain a "body" field.\n The user who created this commen... | from datetime import datetime
import pytest
from src.database.models import User, Comment, Post
from src.schemas import CommentBase
from src.repository import comments as repository_comments
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as a... |
assert response.text == "test_comment"
assert response.user_id == 1
assert response.post_id == 1
@pytest.mark.asyncio
async def test_edit_comment( new_user, session):
"""
The test_edit_comment function tests the edit_comment function in repository_comments.py
The test passes i... | {
"context_start_lineno": 0,
"file": "tests/comments/test_repository_comments.py",
"groundtruth_start_lineno": 100,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 101,
"task_id": "project_cc_python/2897"
} | {
"list": [
{
"filename": "tests/rating/test_repository_ratings.py",
"retrieved_chunk": " :param session: Pass the database session to the function\n :return: A response object\n \"\"\"\n response = await repository_ratings.delete_rate(1, session, new_user)\n assert response.rate == 5\n... | create_comment(1, comment, session, new_user) |
{
"list": [
{
"filename": "src/routes/posts.py",
"retrieved_chunk": " skip (int): The number of posts to skip before returning results. Default is 0.\n limit (int): The maximum number of posts to return per page. Default is 100, max is 1000.\n :param skip: int: Skip a number o... | from datetime import datetime
import pytest
import io
from fastapi import Request, UploadFile
from PIL import Image
from src.database.models import User, Post
import src.repository.posts as repository_posts
from src.schemas import PostUpdate
@pytest.fixture()
def current_user(user, session):
"""
The current... |
assert isinstance(response, list)
assert len(response) >= 1
@pytest.mark.asyncio
async def test_get_post_by_id(post, current_user, session):
"""
The test_get_post_by_id function tests the get_post_by_id function in repository/posts.py
It does this by creating a post, and then calling the get_... | {
"context_start_lineno": 0,
"file": "tests/posts/test_repository_posts.py",
"groundtruth_start_lineno": 135,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 136,
"task_id": "project_cc_python/2906"
} | {
"list": [
{
"filename": "src/routes/posts.py",
"retrieved_chunk": " raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=NOT_FOUND)\n return posts\n@router.get(\"/all\", response_model=List[PostResponse], dependencies=[Depends(allowed_get_all_posts)])\nasync def read_all_posts... | get_my_posts(skip, limit, current_user, session) |
{
"list": [
{
"filename": "tests/hashtags/test_repository_hashtags.py",
"retrieved_chunk": " The test_get_my_tags function tests the get_my_tags function in repository/tag.py\n It creates a new user, and then calls the get_my_tags function with skip=0, limit=100\n The response is chec... | from datetime import datetime
import pytest
from src.database.models import User, Comment, Post
from src.schemas import CommentBase
from src.repository import comments as repository_comments
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as a... |
assert isinstance(response, list)
assert response[0].user_id == 1
@pytest.mark.asyncio
async def test_show_user_post_comments(new_user, session):
"""
The test_show_user_post_comments function tests the show_user_post_comments function in the repository.py file.
The test is successful if i... | {
"context_start_lineno": 0,
"file": "tests/comments/test_repository_comments.py",
"groundtruth_start_lineno": 165,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 166,
"task_id": "project_cc_python/2901"
} | {
"list": [
{
"filename": "tests/hashtags/test_repository_hashtags.py",
"retrieved_chunk": " assert isinstance(response, list)\n assert len(response) >= 1\n@pytest.mark.asyncio\nasync def test_get_all_tags(session):\n \"\"\"\n The test_get_all_tags function tests the get_all_tags function ... | show_user_comments(1, session) |
{
"list": [
{
"filename": "train.py",
"retrieved_chunk": " model.load_state_dict(pretrained_ckpt['model'])\n if config.get('resume', None): \n ckpt = torch.load(config.resume, map_location='cuda:{}'.format(LOCAL_RANK))\n model.load_state_dict(ckpt['model'])\n model = model.... | import torch._C
import torch
import torch.serialization
import onnx
import onnxruntime as rt
import numpy as np
from model.parseq_test import PARSeq
from omegaconf import DictConfig, open_dict, OmegaConf
# args
OUTPUT_FILE = 'parseq_ar_r1.onnx'
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
ckp... |
model._device = torch.device(device)
model = model.eval().to(device)
# print('Model parameters: ', config.model, sep='\n')
# input define
h, w = config.model.img_size
x = torch.randn(1, 3, h, w)
x = x.to(device)
# input test results
out = model(x)
#Onnx export details
dynamic_axes = None
dynamic_export = False
opse... | {
"context_start_lineno": 0,
"file": "pytorch2onnx.py",
"groundtruth_start_lineno": 25,
"repository": "bharatsubedi-PARseq_torch-8ffcb95",
"right_context_start_lineno": 26,
"task_id": "project_cc_python/2941"
} | {
"list": [
{
"filename": "model/utils.py",
"retrieved_chunk": " config.update(exp['model'])\n config.update(kwargs)\n # Workaround for now: manually cast the lr to the correct type.\n config['lr'] = float(config['lr'])\n return config\ndef _get_model_class(key):\n if 'abinet' in... | load_state_dict(torch.load(ckpt_path)['model']) |
{
"list": [
{
"filename": "src/routes/posts.py",
"retrieved_chunk": " skip (int): The number of posts to skip before returning results. Default is 0.\n limit (int): The maximum number of posts to return per page. Default is 100, max is 1000.\n :param skip: int: Skip a number o... | from datetime import datetime
import pytest
import io
from fastapi import Request, UploadFile
from PIL import Image
from src.database.models import User, Post
import src.repository.posts as repository_posts
from src.schemas import PostUpdate
@pytest.fixture()
def current_user(user, session):
"""
The current... |
assert isinstance(response, list)
assert len(response) >= 1
@pytest.mark.asyncio
async def test_get_my_posts(current_user, session):
"""
The test_get_my_posts function tests the get_my_posts function in the repository_posts module.
The test passes if a list of posts is returned and has at least o... | {
"context_start_lineno": 0,
"file": "tests/posts/test_repository_posts.py",
"groundtruth_start_lineno": 118,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 119,
"task_id": "project_cc_python/2905"
} | {
"list": [
{
"filename": "tests/hashtags/test_repository_hashtags.py",
"retrieved_chunk": " assert isinstance(response, list)\n assert len(response) >= 1\n@pytest.mark.asyncio\nasync def test_get_all_tags(session):\n \"\"\"\n The test_get_all_tags function tests the get_all_tags function ... | get_all_posts(skip, limit, session) |
{
"list": [
{
"filename": "pytorch2onnx.py",
"retrieved_chunk": "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\nckpt_path = '/outputs/baseline_all/best_parseq_ckpt.pth'\nconfig_path = '/outputs/baseline_all/config.yaml'\n# config load\nconfig = OmegaConf.load(config_path)\n# co... |
import math
import argparse
from pathlib import Path
from tqdm import tqdm
import time
import os
import sys
import shutil
from omegaconf import OmegaConf
import numpy as np
import string
from typing import List
import torch
from torch.optim import Optimizer
from torch.optim.lr_scheduler import OneCycleLR
import torch... |
device = torch.device('cuda:{}'.format(LOCAL_RANK))
model._device = device
model = DDP(model, device_ids=[LOCAL_RANK], output_device=LOCAL_RANK, find_unused_parameters=True)
estimated_stepping_batches = config.trainer.num_iters
# setting optimizers and schedular
filtered_parameters =... | {
"context_start_lineno": 0,
"file": "train.py",
"groundtruth_start_lineno": 168,
"repository": "bharatsubedi-PARseq_torch-8ffcb95",
"right_context_start_lineno": 169,
"task_id": "project_cc_python/2947"
} | {
"list": [
{
"filename": "pytorch2onnx.py",
"retrieved_chunk": "# model = torch.jit.script(model, example_inputs={model: torch.randn(1, 3, h, w, requires_grad=True)})\nmodel.load_state_dict(torch.load(ckpt_path)['model'])\nmodel._device = torch.device(device)\nmodel = model.eval().to(device)\n# print... | to(LOCAL_RANK) |
{
"list": [
{
"filename": "model/tokenizer_utils.py",
"retrieved_chunk": " super().__init__()\n self.charset = target_charset ###\n self.lowercase_only = target_charset == target_charset.lower()\n self.uppercase_only = target_charset == target_charset.upper()\n# sel... | import glob
import io
import logging
import unicodedata
from pathlib import Path, PurePath
from typing import Callable, Optional, Union, Tuple, List
import random
import numpy as np
import re
import torch
import lmdb
from PIL import Image
import cv2
from torch.utils.data import Dataset, ConcatDataset
from torchvision ... |
if len(label) > max_label_len:
continue
label = charset_adapter(label)
# We filter out samples which don't contain any supported characters
if not label:
continue
# Filter images that are too small.
... | {
"context_start_lineno": 0,
"file": "data/dataset.py",
"groundtruth_start_lineno": 137,
"repository": "bharatsubedi-PARseq_torch-8ffcb95",
"right_context_start_lineno": 138,
"task_id": "project_cc_python/2952"
} | {
"list": [
{
"filename": "model/tokenizer_utils.py",
"retrieved_chunk": " return label\nclass BaseTokenizer(ABC):\n def __init__(self, charset: str, specials_first: tuple = (), specials_last: tuple = ()) -> None:\n self._itos = specials_first + tuple(charset+'[UNK]') + specials_last\... | charset) # edit self.charset in CharsetAdapter |
{
"list": [
{
"filename": "train.py",
"retrieved_chunk": " config.model.charset_train = chars\n config.model.charset_test = config.model.charset_train\n # Special handling for PARseq\n if config.model.get('perm_mirrored', False):\n assert config.model.perm_num % 2 == 0, 'perm_num sh... | from glob import glob
import argparse
import string
import sys
import os
from dataclasses import dataclass
from typing import List
from omegaconf import DictConfig, open_dict, OmegaConf
from tqdm import tqdm
import torch
import string
from data.module import SceneTextDataModule
from model.parseq import PARSeq
@datacla... |
print('Model parameters: ', config.model, sep='\n')
train_dir = os.path.join(args.data_root, 'train')
val_dir = os.path.join(args.data_root, 'valid')
test_dir = os.path.join(args.data_root, 'valid')
datamodule = SceneTextDataModule(root_dir = args.data_root,
... | {
"context_start_lineno": 0,
"file": "test.py",
"groundtruth_start_lineno": 94,
"repository": "bharatsubedi-PARseq_torch-8ffcb95",
"right_context_start_lineno": 95,
"task_id": "project_cc_python/2949"
} | {
"list": [
{
"filename": "train.py",
"retrieved_chunk": " exp_log = SummaryWriter(os.path.join(config.log_dir, 'tf_runs'))\n dist.init_process_group(\"nccl\", rank=WORLD_RANK, world_size=WORLD_SIZE)\n # Balanced data setting\n datamodule = Balanced_Batch(**config.data)\n datamodule.pre... | eval().to(args.device) |
{
"list": [
{
"filename": "train.py",
"retrieved_chunk": " model.load_state_dict(pretrained_ckpt['model'])\n if config.get('resume', None): \n ckpt = torch.load(config.resume, map_location='cuda:{}'.format(LOCAL_RANK))\n model.load_state_dict(ckpt['model'])\n model = model.... | import torch._C
import torch
import torch.serialization
import onnx
import onnxruntime as rt
import numpy as np
from model.parseq_test import PARSeq
from omegaconf import DictConfig, open_dict, OmegaConf
# args
OUTPUT_FILE = 'parseq_ar_r1.onnx'
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
ckp... |
# print('Model parameters: ', config.model, sep='\n')
# input define
h, w = config.model.img_size
x = torch.randn(1, 3, h, w)
x = x.to(device)
# input test results
out = model(x)
#Onnx export details
dynamic_axes = None
dynamic_export = False
opset_version = 14
show = True
#dynamic_axes = {'input' : {0 : 'batch_siz... | {
"context_start_lineno": 0,
"file": "pytorch2onnx.py",
"groundtruth_start_lineno": 27,
"repository": "bharatsubedi-PARseq_torch-8ffcb95",
"right_context_start_lineno": 28,
"task_id": "project_cc_python/2942"
} | {
"list": [
{
"filename": "train.py",
"retrieved_chunk": " filtered_parameters = []\n params_num = []\n for p in filter(lambda p: p.requires_grad, model.parameters()):\n filtered_parameters.append(p)\n params_num.append(np.prod(p.size()))\n print('Trainable params num : ', su... | eval().to(device) |
{
"list": [
{
"filename": "tafrigh/writer.py",
"retrieved_chunk": " for output_format in output_config.output_formats\n ):\n return False\n if (not output_config.save_files_before_compact or output_config.min_words_per_segment != 0) and not all(\n Path(ou... | import logging
from tafrigh.types.transcript_type import TranscriptType
class Config:
def __init__(
self,
urls_or_paths: list[str],
skip_if_output_exist: bool,
playlist_items: str,
verbose: bool,
model_name_or_path: str,
task: str,
language: str,
... |
output_formats.remove(TranscriptType.ALL)
if TranscriptType.NONE in output_formats:
output_formats.remove(TranscriptType.NONE)
self.min_words_per_segment = min_words_per_segment
self.save_files_before_compact = save_files_before_compact
... | {
"context_start_lineno": 0,
"file": "tafrigh/config.py",
"groundtruth_start_lineno": 104,
"repository": "ieasybooks-tafrigh-4aece79",
"right_context_start_lineno": 105,
"task_id": "project_cc_python/2934"
} | {
"list": [
{
"filename": "tafrigh/writer.py",
"retrieved_chunk": " with open(file_path, 'w', encoding='utf-8') as fp:\n fp.write(content)",
"score": 39.09685285590472
},
{
"filename": "tafrigh/writer.py",
"retrieved_chunk": " if not output_config.sav... | ALL in output_formats: |
{
"list": [
{
"filename": "train.py",
"retrieved_chunk": " config.model.charset_train = chars\n config.model.charset_test = config.model.charset_train\n # Special handling for PARseq\n if config.model.get('perm_mirrored', False):\n assert config.model.perm_num % 2 == 0, 'perm_num sh... | from glob import glob
import argparse
import string
import sys
import os
from dataclasses import dataclass
from typing import List
from omegaconf import DictConfig, open_dict, OmegaConf
from tqdm import tqdm
import torch
import string
from data.module import SceneTextDataModule
from model.parseq import PARSeq
@datacla... |
model._device = args.device
model = model.eval().to(args.device)
print('Model parameters: ', config.model, sep='\n')
train_dir = os.path.join(args.data_root, 'train')
val_dir = os.path.join(args.data_root, 'valid')
test_dir = os.path.join(args.data_root, 'valid')
datamodule = Sce... | {
"context_start_lineno": 0,
"file": "test.py",
"groundtruth_start_lineno": 92,
"repository": "bharatsubedi-PARseq_torch-8ffcb95",
"right_context_start_lineno": 93,
"task_id": "project_cc_python/2948"
} | {
"list": [
{
"filename": "train.py",
"retrieved_chunk": " exp_log = SummaryWriter(os.path.join(config.log_dir, 'tf_runs'))\n dist.init_process_group(\"nccl\", rank=WORLD_RANK, world_size=WORLD_SIZE)\n # Balanced data setting\n datamodule = Balanced_Batch(**config.data)\n datamodule.pre... | load_state_dict(torch.load(args.checkpoint)['model']) |
{
"list": [
{
"filename": "src/repository/posts.py",
"retrieved_chunk": "async def get_post_by_keyword(keyword: str, db: Session):\n \"\"\"\n The get_post_by_keyword function returns a list of posts that match the keyword.\n The keyword is searched in both the title and description fields... | from datetime import datetime
import pytest
import io
from fastapi import Request, UploadFile
from PIL import Image
from src.database.models import User, Post
import src.repository.posts as repository_posts
from src.schemas import PostUpdate
@pytest.fixture()
def current_user(user, session):
"""
The current... |
assert isinstance(response, list)
assert response[0].title == "test_post"
assert response[0].descr == "test_post"
assert response[0].id == post.id
@pytest.mark.asyncio
async def test_update_post(post, body, current_user, session):
"""
The test_update_post function tests the update_post functi... | {
"context_start_lineno": 0,
"file": "tests/posts/test_repository_posts.py",
"groundtruth_start_lineno": 268,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 269,
"task_id": "project_cc_python/2914"
} | {
"list": [
{
"filename": "tests/hashtags/test_route_hashtags.py",
"retrieved_chunk": " with patch.object(auth_service, 'redis_cache') as r_mock:\n r_mock.get.return_value = None\n response = client.put(f'/api/hashtags/upd_tag/{tag.id}',\n json={\"title\": \... | get_post_by_keyword(keyword, session) |
{
"list": [
{
"filename": "tests/comments/test_repository_comments.py",
"retrieved_chunk": "async def test_show_user_comments(new_user, session):\n \"\"\"\n The test_show_user_comments function tests the show_user_comments function in repository_comments.py\n It does this by creating a ne... | from datetime import datetime
import pytest
from src.database.models import User, Post, Rating
from src.repository import ratings as repository_ratings
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.
It then queries the datab... |
assert response.rate == 5
assert response.user_id == 1
assert response.post_id == 1
@pytest.mark.asyncio
async def test_show_ratings(rating, new_user, session):
"""
The test_show_ratings function tests the show_ratings function in repository_ratings.py
It checks if the response is... | {
"context_start_lineno": 0,
"file": "tests/rating/test_repository_ratings.py",
"groundtruth_start_lineno": 132,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 133,
"task_id": "project_cc_python/2922"
} | {
"list": [
{
"filename": "tests/comments/test_repository_comments.py",
"retrieved_chunk": " assert isinstance(response, list)\n assert response[0].user_id == 1\n@pytest.mark.asyncio\nasync def test_show_user_post_comments(new_user, session):\n \"\"\"\n The test_show_user_post_comments fun... | delete_rate(1, session, new_user) |
{
"list": [
{
"filename": "src/routes/hashtags.py",
"retrieved_chunk": " :param current_user: User: Get the user that is currently logged in\n :return: A list of tag objects\n \"\"\"\n tags = await repository_tags.get_my_tags(skip, limit, current_user, db)\n return tags\n@router.get(\"/... | from datetime import datetime
import pytest
from unittest.mock import patch
import src.repository.hashtags as repository_tag
from src.database.models import User, Hashtag
from src.schemas import HashtagBase
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a se... |
assert isinstance(response, list)
assert len(response) >= 1
@pytest.mark.asyncio
async def test_get_all_tags(session):
"""
The test_get_all_tags function tests the get_all_tags function in the repository_tag.py file.
The test passes if it is able to retrieve a list of tags from the database.
... | {
"context_start_lineno": 0,
"file": "tests/hashtags/test_repository_hashtags.py",
"groundtruth_start_lineno": 107,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 108,
"task_id": "project_cc_python/2928"
} | {
"list": [
{
"filename": "src/routes/hashtags.py",
"retrieved_chunk": " The function takes two optional parameters: skip and limit, which are used to paginate the results.\n If no parameters are provided, then it will return up to 100 tags starting from the first tag.\n :param skip: ... | get_my_tags(skip, limit, new_user, session) |
{
"list": [
{
"filename": "tests/comments/test_repository_comments.py",
"retrieved_chunk": "async def test_show_user_comments(new_user, session):\n \"\"\"\n The test_show_user_comments function tests the show_user_comments function in repository_comments.py\n It does this by creating a ne... | from datetime import datetime
import pytest
from src.database.models import User, Post, Rating
from src.repository import ratings as repository_ratings
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.
It then queries the datab... |
assert response.rate == 4
assert response.user_id == 1
assert response.post_id == 1
@pytest.mark.asyncio
async def test_edit_rate(new_user, session):
"""
The test_edit_rate function tests the edit_rate function in repository_ratings.py
It checks if the rate is 5, user id is 1 and ... | {
"context_start_lineno": 0,
"file": "tests/rating/test_repository_ratings.py",
"groundtruth_start_lineno": 98,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 99,
"task_id": "project_cc_python/2920"
} | {
"list": [
{
"filename": "tests/transformations/test_repository_transform_post.py",
"retrieved_chunk": " :param new_user: Create a new user in the database\n :param session: Create a new session for the user\n :return: A string\n \"\"\"\n response = await show_qr(post.id, new_user, ses... | create_rate(1, 4, session, new_user) |
{
"list": [
{
"filename": "src/repository/ratings.py",
"retrieved_chunk": "async def show_ratings(db: Session, user: User) -> list[Type[Rating]]:\n \"\"\"\n The show_ratings function returns a list of all ratings in the database.\n Args:\n db (Session): The database session to ... | from datetime import datetime
import pytest
from src.database.models import User, Post, Rating
from src.repository import ratings as repository_ratings
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.
It then queries the datab... |
assert isinstance(response, list)
assert response[0].rate == 4
assert response[0].user_id == 1
@pytest.mark.asyncio
async def test_show_my_ratings(new_user, session):
"""
The test_show_my_ratings function tests the show_my_ratings function in repository_ratings.py
The test passes ... | {
"context_start_lineno": 0,
"file": "tests/rating/test_repository_ratings.py",
"groundtruth_start_lineno": 149,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 150,
"task_id": "project_cc_python/2923"
} | {
"list": [
{
"filename": "src/repository/ratings.py",
"retrieved_chunk": " all_ratings = db.query(Rating).all()\n return all_ratings\nasync def show_my_ratings(db: Session, user: User) -> list[Type[Rating]]:\n \"\"\"\n The show_ratings function returns a list of all ratings in the databas... | show_ratings(session, new_user) |
{
"list": [
{
"filename": "src/routes/ratings.py",
"retrieved_chunk": " The user_rate_post function allows a user to rate a post.\n The function takes in the user_id and post_id as parameters, along with the database session and current user.\n If no rating is found, an HTTPException ... | from datetime import datetime
import pytest
from src.database.models import User, Post, Rating
from src.repository import ratings as repository_ratings
@pytest.fixture()
def new_user(user, session):
"""
The new_user function takes a user object and a session object as arguments.
It then queries the datab... |
assert response.rate == 4
assert response.user_id == 1
assert response.post_id == 1
| {
"context_start_lineno": 0,
"file": "tests/rating/test_repository_ratings.py",
"groundtruth_start_lineno": 179,
"repository": "ortursucceeh-Project-PhotoShare-1942d61",
"right_context_start_lineno": 180,
"task_id": "project_cc_python/2925"
} | {
"list": [
{
"filename": "tests/users/test_repository_users.py",
"retrieved_chunk": " :return: A list of all liked posts for a user\n \"\"\"\n response = await repository_users.get_all_liked_posts(new_user, session)\n assert isinstance(response, list)\n assert len(response) == 0\n@pyte... | user_rate_post(1, 1, session, new_user) |
{
"list": [
{
"filename": "Step3-Tumor-Segmentation/train.py",
"retrieved_chunk": " ADC = ADC.view(-1, 1, l, w, e).to(device)\n T2W = T2W.view(-1, 1, l, w, e).to(device)\n Infor_DCE = Infor_DCE.view(-1, 1, l, w, e).to(device)\n Infor_ADC = Infor_ADC.view(-1, 1, l, w, e).to(... | import torch
import numpy as np
import torch.optim as optim
from options.Options import Options_x
from dataset.dataset_lits_train import Lits_DataSet
from dataset.dataset_lits_val import Val_DataSet
from Model.runet import RUnet
from torch.utils.data import DataLoader
from setting.common import adjust_learning_rate
fr... |
time_elapsed = time.time() - since
print("=======Train Epoch:{}======Learning_rate:{}======Train complete in {:.0f}m {:.0f}s=======".format(epoch, optimizer.param_groups[0]['lr'], time_elapsed // 60, time_elapsed % 60))
return OrderedDict({'Loss': Loss.avg})
def val(val_dataloader, epoch):
since =... | {
"context_start_lineno": 0,
"file": "Step1-Image-Synthesis/train.py",
"groundtruth_start_lineno": 41,
"repository": "ZhangJD-ong-MoSID-Breast-Tumor-Segmentation-from-Multi-parametric-MRI-e826e12",
"right_context_start_lineno": 42,
"task_id": "project_cc_python/2957"
} | {
"list": [
{
"filename": "Step3-Tumor-Segmentation/train.py",
"retrieved_chunk": " pred = model(DCE, sub, ADC, T2W, Infor_DCE, Infor_ADC, Infor_T2)\n Dice_loss = dice_loss(pred, gt)\n Bce_loss = bce_loss(pred, gt)\n loss = Bce_loss + 5 * Dice_loss\n Loss.update(loss... | update(loss.item(), ADC.size(0)) |
{
"list": [
{
"filename": "Step2-Modality-Specific-Information-Disentanglement/main.py",
"retrieved_chunk": " DCE = DCE.view(-1, 1, l, w, e).to(device)\n sub = sub.view(-1, 1, l, w, e).to(device)\n ADC = ADC.view(-1, 1, l, w, e).to(device)\n T2W = T2W.view(-1, 1, l, w, e).t... | import torch
import numpy as np
import torch.optim as optim
from options.Options import Options_x
from dataset.dataset_lits_train import Lits_DataSet
from dataset.dataset_lits_val import Val_DataSet
from Model.networks import MoSID
from torch.utils.data import DataLoader
from utils.common import adjust_learning_rate
fr... |
DICE_Loss.update(Dice_loss.item(), DCE.size(0))
BCE_Loss.update(Bce_loss.item(), DCE.size(0))
time_elapsed = time.time() - since
print("=======Val Epoch:{}======Learning_rate:{}======Validate complete in {:.0f}m {:.0f}s=======".format(epoch, optimizer.param_groups[0]['lr'], time_elapsed // 60, ... | {
"context_start_lineno": 0,
"file": "Step3-Tumor-Segmentation/train.py",
"groundtruth_start_lineno": 42,
"repository": "ZhangJD-ong-MoSID-Breast-Tumor-Segmentation-from-Multi-parametric-MRI-e826e12",
"right_context_start_lineno": 43,
"task_id": "project_cc_python/2967"
} | {
"list": [
{
"filename": "Step2-Modality-Specific-Information-Disentanglement/main.py",
"retrieved_chunk": " loss = Bce_loss + 5 * Dice_loss\n optimizer.zero_grad()\n loss.backward()\n optimizer.step()\n Loss.update(loss.item(), DCE0.size(0))\n DICE_Loss.upda... | update(loss.item(), DCE.size(0)) |
{
"list": [
{
"filename": "Step3-Tumor-Segmentation/train.py",
"retrieved_chunk": " ADC = ADC.view(-1, 1, l, w, e).to(device)\n T2W = T2W.view(-1, 1, l, w, e).to(device)\n Infor_DCE = Infor_DCE.view(-1, 1, l, w, e).to(device)\n Infor_ADC = Infor_ADC.view(-1, 1, l, w, e).to(... | import torch
import numpy as np
import torch.optim as optim
from options.Options import Options_x
from dataset.dataset_lits_train import Lits_DataSet
from dataset.dataset_lits_val import Val_DataSet
from Model.networks import RUnet
from torch.utils.data import DataLoader
from setting.common import adjust_learning_rate
... |
DICE_Loss.update(Dice_loss.item(), DCE0.size(0))
BCE_Loss.update(Bce_loss.item(), DCE0.size(0))
pred_adc = model(torch.cat((DCE, sub, ADC_syn, T2W), dim=1))
Dice_loss1 = dice_loss(pred_adc, gt)
Bce_loss1 = bce_loss(pred_adc, gt)
loss1 = Bce_loss1 + 5 * Dice_loss1
... | {
"context_start_lineno": 0,
"file": "Step2-Modality-Specific-Information-Disentanglement/main.py",
"groundtruth_start_lineno": 42,
"repository": "ZhangJD-ong-MoSID-Breast-Tumor-Segmentation-from-Multi-parametric-MRI-e826e12",
"right_context_start_lineno": 43,
"task_id": "project_cc_python/2977"
} | {
"list": [
{
"filename": "Step3-Tumor-Segmentation/train.py",
"retrieved_chunk": " optimizer.zero_grad()\n loss.backward()\n optimizer.step()\n adjust_learning_rate(optimizer, epoch, opt)\n Loss.update(loss.item(), DCE.size(0))\n DICE_Loss.update(Dice_loss.it... | update(loss.item(), DCE0.size(0)) |
{
"list": [
{
"filename": "Step3-Tumor-Segmentation/test.py",
"retrieved_chunk": " sub = sub.unsqueeze(1).type(torch.float32)\n adc = adc.unsqueeze(1).type(torch.float32)\n t2w = t2w.unsqueeze(1).type(torch.float32)\n p_all_fake = p_all_fake.... | import torch
import gc
import numpy as np
import SimpleITK as sitk
from options.Options import Options_x
from tqdm import tqdm
from Model.networks import RUnet
from torch.utils.data import DataLoader
from setting import logger, util
from setting.metrics import seg_metric
import os
from dataset.dataset_lits_test import ... |
save_tool.add_result(seg.detach().cpu())
probility = save_prob_tool.recompone_overlap()
pred = save_tool.recompone_overlap()
recon = (pred.numpy() > 0.5).astype(np.uint16) * mask.astype(np.uint16)
gt = load(os.path.join(opt.datapath, file_idx, 'GT.nii.gz'))
DSC... | {
"context_start_lineno": 0,
"file": "Step2-Modality-Specific-Information-Disentanglement/test.py",
"groundtruth_start_lineno": 61,
"repository": "ZhangJD-ong-MoSID-Breast-Tumor-Segmentation-from-Multi-parametric-MRI-e826e12",
"right_context_start_lineno": 62,
"task_id": "project_cc_python/2983"
} | {
"list": [
{
"filename": "Step3-Tumor-Segmentation/test.py",
"retrieved_chunk": " recon = (pred.numpy() > 0.5).astype(np.uint16)\n pred_coarse = load(os.path.join(opt.datapath, file_idx, 'pred_coarse.nii.gz'))\n pred_coarse[crop_box[0, 0]:crop_box[0, 1], crop_box[1, 0]:crop_box[1... | add_result(probility.detach().cpu()) |
{
"list": [
{
"filename": "npc_gzip/distance.py",
"retrieved_chunk": " >>> import random\n >>> a = random.random()\n >>> b = random.random()\n >>> ab = random.random()\n >>> distance = Distance(a, b, ab)\n >>> ncd: float = distance._ncd(a, b, ab)\n >>> cdm: float = distance._cdm(a... | import random
import numpy as np
import pytest
from npc_gzip.distance import Distance
from npc_gzip.exceptions import CompressedValuesEqualZero, InvalidShapeException
class TestDistance:
array_a = np.random.rand(3, 10)
array_b = np.random.rand(3, 10)
array_ab = np.random.rand(3, 10)
float_a = rando... |
assert isinstance(out, float)
a = b = ab = 0
with pytest.raises(CompressedValuesEqualZero):
distance._cdm(a, b, ab)
with pytest.raises(ValueError):
distance._ncd(self.array_a, self.array_b, self.array_ab)
def test__clm(self) -> None:
distance = Dis... | {
"context_start_lineno": 0,
"file": "tests/test_distance.py",
"groundtruth_start_lineno": 52,
"repository": "bazingagin-npc_gzip-928659e",
"right_context_start_lineno": 53,
"task_id": "project_cc_python/3067"
} | {
"list": [
{
"filename": "npc_gzip/distance.py",
"retrieved_chunk": " >>> assert isinstance(cdm, float)\n >>> assert isinstance(clm, float)\n >>> assert isinstance(mse, float)\n >>> a = np.random.rand(3, 10)\n >>> b = np.random.rand(3, 10)\n >>> ab = np.random.rand(3, 10)\n >>> d... | _cdm(self.float_a, self.float_b, self.float_ab) |
{
"list": [
{
"filename": "Step3-Tumor-Segmentation/test.py",
"retrieved_chunk": " print(\"using {} device.\".format(device))\n model = MoSID().to(device)\n ckpt = torch.load(opt.checkpoints_dir + '/' + opt.task_name + '/model/' + model_name, map_location=device)\n model.load_state_dict(ck... | import torch
import gc
import numpy as np
import SimpleITK as sitk
from options.Options import Options_x
from tqdm import tqdm
from Model.networks import RUnet
from torch.utils.data import DataLoader
from setting import logger, util
from setting.metrics import seg_metric
import os
from dataset.dataset_lits_test import ... |
cut_param = {'patch_s': opt.patch_size[0], 'patch_h': opt.patch_size[1], 'patch_w': opt.patch_size[2],
'stride_s': opt.patch_stride[0], 'stride_h': opt.patch_stride[1], 'stride_w': opt.patch_stride[2]}
datasets = Test_all_Datasets(opt.datapath, cut_param, flag)
for img_dataset, original_... | {
"context_start_lineno": 0,
"file": "Step2-Modality-Specific-Information-Disentanglement/test.py",
"groundtruth_start_lineno": 37,
"repository": "ZhangJD-ong-MoSID-Breast-Tumor-Segmentation-from-Multi-parametric-MRI-e826e12",
"right_context_start_lineno": 38,
"task_id": "project_cc_python/2982"
} | {
"list": [
{
"filename": "Step3-Tumor-Segmentation/test.py",
"retrieved_chunk": " datasets = Test_all_Datasets(opt.datapath, cut_param)\n for img_dataset, original_shape, new_shape, mask, file_idx, crop_box in datasets:\n save_tool = Recompone_tool(original_shape, new_shape, cut_param)\n... | Test_Logger(save_excel_path, "results_train") |
{
"list": [
{
"filename": "npc_gzip/exceptions.py",
"retrieved_chunk": " function_name: Optional[str] = None,\n ) -> None:\n self.message = f\"\"\"\n The passed values must either all of the same shape.\n arg1: {array_a.shape}\n arg2: {array_b.shape}\n ... | import random
import numpy as np
import pytest
from npc_gzip.distance import Distance
from npc_gzip.exceptions import CompressedValuesEqualZero, InvalidShapeException
class TestDistance:
array_a = np.random.rand(3, 10)
array_b = np.random.rand(3, 10)
array_ab = np.random.rand(3, 10)
float_a = rando... |
assert isinstance(out, float)
a = b = ab = 0
with pytest.raises(CompressedValuesEqualZero):
distance._ncd(a, b, ab)
with pytest.raises(ValueError):
distance._ncd(self.array_a, self.array_b, self.array_ab)
def test__cdm(self) -> None:
distance = Dis... | {
"context_start_lineno": 0,
"file": "tests/test_distance.py",
"groundtruth_start_lineno": 40,
"repository": "bazingagin-npc_gzip-928659e",
"right_context_start_lineno": 41,
"task_id": "project_cc_python/3066"
} | {
"list": [
{
"filename": "tests/test_knn_classifier.py",
"retrieved_chunk": " 1,\n self.model.training_inputs.shape[0],\n )\n assert labels.shape == (1,)\n assert similar_samples.shape == (top_k, 1)\n test_set_size = random.randint(2, 50)\n tes... | _ncd(self.float_a, self.float_b, self.float_ab) |
{
"list": [
{
"filename": "npc_gzip/distance.py",
"retrieved_chunk": " >>> import random\n >>> a = random.random()\n >>> b = random.random()\n >>> ab = random.random()\n >>> distance = Distance(a, b, ab)\n >>> ncd: float = distance._ncd(a, b, ab)\n >>> cdm: float = distance._cdm(a... | import random
import numpy as np
import pytest
from npc_gzip.distance import Distance
from npc_gzip.exceptions import CompressedValuesEqualZero, InvalidShapeException
class TestDistance:
array_a = np.random.rand(3, 10)
array_b = np.random.rand(3, 10)
array_ab = np.random.rand(3, 10)
float_a = rando... |
assert isinstance(out, float)
a = b = 0
out = distance._mse(a, b)
assert isinstance(out, float)
def test_ncd(self) -> None:
distance = Distance(self.float_a, self.float_b, self.float_ab)
out = distance.ncd
assert isinstance(out, np.ndarray)
distanc... | {
"context_start_lineno": 0,
"file": "tests/test_distance.py",
"groundtruth_start_lineno": 76,
"repository": "bazingagin-npc_gzip-928659e",
"right_context_start_lineno": 77,
"task_id": "project_cc_python/3069"
} | {
"list": [
{
"filename": "npc_gzip/distance.py",
"retrieved_chunk": " >>> assert isinstance(cdm, float)\n >>> assert isinstance(clm, float)\n >>> assert isinstance(mse, float)\n >>> a = np.random.rand(3, 10)\n >>> b = np.random.rand(3, 10)\n >>> ab = np.random.rand(3, 10)\n >>> d... | _mse(self.float_a, self.float_b) |
{
"list": [
{
"filename": "npc_gzip/distance.py",
"retrieved_chunk": " >>> import random\n >>> a = random.random()\n >>> b = random.random()\n >>> ab = random.random()\n >>> distance = Distance(a, b, ab)\n >>> ncd: float = distance._ncd(a, b, ab)\n >>> cdm: float = distance._cdm(a... | import random
import numpy as np
import pytest
from npc_gzip.distance import Distance
from npc_gzip.exceptions import CompressedValuesEqualZero, InvalidShapeException
class TestDistance:
array_a = np.random.rand(3, 10)
array_b = np.random.rand(3, 10)
array_ab = np.random.rand(3, 10)
float_a = rando... |
assert isinstance(out, float)
a = b = ab = 0
with pytest.raises(CompressedValuesEqualZero):
distance._clm(a, b, ab)
with pytest.raises(ValueError):
distance._ncd(self.array_a, self.array_b, self.array_ab)
def test__mse(self) -> None:
distance = Dis... | {
"context_start_lineno": 0,
"file": "tests/test_distance.py",
"groundtruth_start_lineno": 64,
"repository": "bazingagin-npc_gzip-928659e",
"right_context_start_lineno": 65,
"task_id": "project_cc_python/3068"
} | {
"list": [
{
"filename": "npc_gzip/distance.py",
"retrieved_chunk": " >>> assert isinstance(cdm, float)\n >>> assert isinstance(clm, float)\n >>> assert isinstance(mse, float)\n >>> a = np.random.rand(3, 10)\n >>> b = np.random.rand(3, 10)\n >>> ab = np.random.rand(3, 10)\n >>> d... | _clm(self.float_a, self.float_b, self.float_ab) |
{
"list": [
{
"filename": "viper2/core/sessions.py",
"retrieved_chunk": "# pylint: disable=too-few-public-methods\nclass Session:\n def __init__(self) -> None:\n self.identifier: int\n self.file: FileObject\n self.created_at = datetime.datetime.fromtimestamp(time.time()).strfti... | # Copyright 2023 The viper2 Authors. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
import logging
import os
from .database import init_db
from .storage import Storage
log = logging.getLogger("viper")
PROJECT_DEFAULT = "default"
# pylint:... |
if not os.path.exists(self.path):
os.makedirs(self.path)
init_db(os.path.join(self.path, "viper.db"))
def is_default(self) -> bool:
if self.name == PROJECT_DEFAULT:
return True
return False
class Projects:
def __init__(self) -> None:
self.cu... | {
"context_start_lineno": 0,
"file": "viper2/core/projects.py",
"groundtruth_start_lineno": 22,
"repository": "viper-framework-viper2-bd8aa34",
"right_context_start_lineno": 23,
"task_id": "project_cc_python/3062"
} | {
"list": [
{
"filename": "viper2/core/sessions.py",
"retrieved_chunk": " self.current: Optional[Session] = None\n self.__sessions: List[Session] = []\n # This is used to keep trace of the results from the last \"find\" command\n # so we can reference them in other commands... | projects_path, self.name) |
{
"list": [
{
"filename": "viper2/core/sessions.py",
"retrieved_chunk": " self.current = session\n def new(self, file_path: str) -> None:\n file_object = FileObject(file_path)\n for session in self.__sessions:\n if session.file and session.file.path == file_path:\n ... | # Copyright 2023 The viper2 Authors. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
import os
from platformdirs import user_data_dir
from viper2 import printer
from ..common.file import FileObject
class Storage:
def __init__(self) -> ... |
return file_path
def get_file_path(self, project_path: str, sha256: str) -> str:
file_path = os.path.join(
project_path, "files", sha256[0], sha256[1], sha256[2], sha256[3], sha256
)
if not os.path.exists(file_path):
return ""
return file_path
| {
"context_start_lineno": 0,
"file": "viper2/core/storage.py",
"groundtruth_start_lineno": 41,
"repository": "viper-framework-viper2-bd8aa34",
"right_context_start_lineno": 42,
"task_id": "project_cc_python/3060"
} | {
"list": [
{
"filename": "viper2/core/sessions.py",
"retrieved_chunk": " if not os.path.exists(file_object.path):\n printer.error(\"File does not exist at path %s\", file_object.path)\n return\n session = Session()\n session.identifier = len(self.__sessions)... | success("Successfully stored file in repository") |
{
"list": [
{
"filename": "viper2/core/sessions.py",
"retrieved_chunk": " if not os.path.exists(file_object.path):\n printer.error(\"File does not exist at path %s\", file_object.path)\n return\n session = Session()\n session.identifier = len(self.__sessions)... | # Copyright 2023 The viper2 Authors. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
import importlib
import inspect
import os
import pkgutil
import shutil
import sys
import tempfile
from pipreqs import pipreqs # type: ignore
from viper2 imp... |
return
sys.path.insert(0, modules_path)
for _, module_name, ispkg in pkgutil.iter_modules([modules_path]):
if ispkg:
continue
module_path = os.path.join(modules_path, f"{module_name}.py")
dependencies = get_module_dependencies(module_path)
can_import = True... | {
"context_start_lineno": 0,
"file": "viper2/core/modules.py",
"groundtruth_start_lineno": 50,
"repository": "viper-framework-viper2-bd8aa34",
"right_context_start_lineno": 51,
"task_id": "project_cc_python/3058"
} | {
"list": [
{
"filename": "viper2/ui/__init__.py",
"retrieved_chunk": " cmd.run()\n elif cmd_name in modules:\n mod = modules[cmd_name][\"class\"]()\n mod.add_args(*cmd_args)\n mod.run()\n else:\n printer.error('No module or command found for \"%s\"', cmd_name)... | error("The modules directory does not exist at path: %s", modules_path) |
{
"list": [
{
"filename": "viper2/core/projects.py",
"retrieved_chunk": "class Project:\n def __init__(self, name: str) -> None:\n self.name = name\n if self.name == PROJECT_DEFAULT:\n self.path = Storage().root_path\n else:\n self.path = os.path.join(Stor... | # Copyright 2023 The viper2 Authors. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
import os
from platformdirs import user_data_dir
from viper2 import printer
from ..common.file import FileObject
class Storage:
def __init__(self) -> ... |
return ""
file_dir = os.path.join(
project_path, "files", sha256[0], sha256[1], sha256[2], sha256[3]
)
if not os.path.exists(file_dir):
os.makedirs(file_dir)
file_path = os.path.join(file_dir, sha256)
if os.path.exists(file_path):
... | {
"context_start_lineno": 0,
"file": "viper2/core/storage.py",
"groundtruth_start_lineno": 21,
"repository": "viper-framework-viper2-bd8aa34",
"right_context_start_lineno": 22,
"task_id": "project_cc_python/3059"
} | {
"list": [
{
"filename": "viper2/core/projects.py",
"retrieved_chunk": " def is_default(self) -> bool:\n if self.name == PROJECT_DEFAULT:\n return True\n return False\nclass Projects:\n def __init__(self) -> None:\n self.current = Project(PROJECT_DEFAULT)\n de... | error("The file does not have a valid sha256 hash") |
{
"list": [
{
"filename": "viper2/ui/shell.py",
"retrieved_chunk": " def help(self) -> None:\n rows = [\n [\"help\", \"Display this help message\"],\n [\"clear\", \"Clear the screen\"],\n [\"exit, quit\", \"Exit from the Viper shell\"],\n ]\n fo... | # Copyright 2023 The viper2 Authors. All rights reserved.
# Use of this source code is governed by a BSD-style
# license that can be found in the LICENSE file.
import platform
import sys
from viper2 import printer
from viper2.common.version import VIPER_VERSION
from .command import Command
class About(Command):
... | {
"context_start_lineno": 0,
"file": "viper2/ui/cmd/about.py",
"groundtruth_start_lineno": 23,
"repository": "viper-framework-viper2-bd8aa34",
"right_context_start_lineno": 24,
"task_id": "project_cc_python/3056"
} | {
"list": [
{
"filename": "viper2/ui/shell.py",
"retrieved_chunk": " print(\"\")\n if len(self.__modules) == 0:\n printer.info(\"No modules available\")\n return\n rows = []\n for module_name, module_properties in self.__modules.items():\n r... | table(columns=["Key", "Value"], rows=rows) | |
{
"list": [
{
"filename": "action_constrained_rl/constraint/quadratic_constraint.py",
"retrieved_chunk": "from .power_constraint import make_compatible\nclass QuadraticConstraint(Constraint):\n \"\"\"\n State-dependent Action Constraints with the from\n $`\\sum Q_ij a_i a_j \\leq M`$ \n \"... | # Copyright (c) 2023 OMRON SINIC X Corporation
# Author: Shuwa Miura, Kazumi Kasaura
from .quadratic_constraint import QuadraticConstraint
import torch as th
import cvxpy as cp
import gurobipy as gp
import math
from ..cvxpy_variables import CVXPYVariables
from .power_constraint import make_compatible
class Sin2Const... |
for i in range(self.a_dim):
sin2 = th.sin(states[:,self.index[i]])**2
Q[:,i,i] = sin2
return Q
def cvxpy_constraints(self, x, state = None):
pass
def gp_constraints(self, model, x, s):
Sq = gp.QuadExpr()
for i in range(self.a_dim):
... | {
"context_start_lineno": 0,
"file": "action_constrained_rl/constraint/sin2_constraint.py",
"groundtruth_start_lineno": 24,
"repository": "omron-sinicx-action-constrained-RL-benchmark-47b85fb",
"right_context_start_lineno": 25,
"task_id": "project_cc_python/3009"
} | {
"list": [
{
"filename": "action_constrained_rl/constraint/quadratic_constraint.py",
"retrieved_chunk": " @abstractmethod\n def getTensorQ(self, state):\n pass\n def getQ(self, state):\n if isinstance(state, np.ndarray):\n return self.getTensorQ(to_tensors(state)).nu... | a_dim,self.a_dim),device = states.device) |
{
"list": [
{
"filename": "mtrl/mtrl_files/sdmgrad.py",
"retrieved_chunk": " def __init__(\n self,\n env_obs_shape: List[int],\n action_shape: List[int],\n action_range: Tuple[int, int],\n device: torch.device,\n agent_cfg: ConfigType,\n multitask_cf... | # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
"""Code to interface with the config."""
import datetime
import hashlib
import os
from copy import deepcopy
from typing import Any, Dict, cast
import hydra
from omegaconf import OmegaConf
from mtrl.utils import utils
from mtrl.utils.types import C... |
return config
def pretty_print(config, resolve: bool = True):
"""Prettyprint the config.
Args:
config ([type]):
resolve (bool, optional): should resolve the config before printing. Defaults to True.
"""
print(OmegaConf.to_yaml(config, resolve=resolve))
def get_env_params_from_c... | {
"context_start_lineno": 0,
"file": "mtrl/mtrl_files/config.py",
"groundtruth_start_lineno": 184,
"repository": "ml-opt-lab-sdmgrad-86963c6",
"right_context_start_lineno": 185,
"task_id": "project_cc_python/3077"
} | {
"list": [
{
"filename": "mtrl/mtrl_files/sdmgrad.py",
"retrieved_chunk": " ):\n \"\"\"Regularized gradient algorithm.\"\"\"\n agent_cfg_copy = deepcopy(agent_cfg)\n del agent_cfg_copy['sdmgrad_lmbda']\n del agent_cfg_copy['sdmgrad_method']\n OmegaConf.set_struct... | make_dir(path=config.experiment.save_dir) |
{
"list": [
{
"filename": "action_constrained_rl/constraint/sin2_constraint.py",
"retrieved_chunk": " \"\"\"\n State-dependent Action Constraints with the from\n $\\sum a_i^2\\sin^2\\theta_i \\leq M$ where $\\theta_i$ is the angle corresponding to $a_i$\n \"\"\"\n def __init__(self, in... | # Copyright (c) 2023 OMRON SINIC X Corporation
# Author: Shuwa Miura, Kazumi Kasaura
from .constraint import LinearConstraint
import torch
import cvxpy as cp
import gurobipy as gp
from ..cvxpy_variables import CVXPYVariables
def make_compatible(a, b):
if a.device != b.device:
a=a.to(b.device)
if a.dt... |
self.scale = scale
self.s_dim = s_dim
for i in range(2 ** self.a_dim):
for j in range(self.a_dim):
if i // (2 ** j) % 2 == 0:
self.K[i,j] = scale[j]
else:
self.K[i,j] = -scale[j]
self.max_power = max_pow... | {
"context_start_lineno": 0,
"file": "action_constrained_rl/constraint/power_constraint.py",
"groundtruth_start_lineno": 93,
"repository": "omron-sinicx-action-constrained-RL-benchmark-47b85fb",
"right_context_start_lineno": 94,
"task_id": "project_cc_python/2994"
} | {
"list": [
{
"filename": "action_constrained_rl/constraint/sin2_constraint.py",
"retrieved_chunk": " sin2 = th.sin(states[:,self.index[i]])**2\n Q[:,i,i] = sin2\n return Q\n def cvxpy_constraints(self, x, state = None):\n pass\n def gp_constraints(self, model... | a_dim, self.a_dim)) |
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