repo stringlengths 1 99 | file stringlengths 13 215 | code stringlengths 12 59.2M | file_length int64 12 59.2M | avg_line_length float64 3.82 1.48M | max_line_length int64 12 2.51M | extension_type stringclasses 1
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|---|---|---|---|---|---|---|
ImgX-DiffSeg | ImgX-DiffSeg-main/imgx/exp/mixed_precision.py | """Mixed precision related functions."""
from functools import partial
import chex
import haiku as hk
import jax
import jax.numpy as jnp
import jmp
from imgx import model
from imgx.model import CONFIG_NAME_TO_MODEL_CLS_NAME
def get_mixed_precision_policy(use_mp: bool) -> jmp.Policy:
"""Return general mixed prec... | 2,956 | 29.173469 | 78 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/imgx/exp/eval.py | """Module for building evaluation functions."""
import json
from functools import partial
from pathlib import Path
from typing import Callable, Dict, Iterable, Optional, Tuple
import chex
import haiku as hk
import jax
import numpy as np
import pandas as pd
from jax import numpy as jnp
from omegaconf import DictConfig
... | 16,503 | 31.746032 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_model_basic.py | """Test basic functions for model."""
import chex
import jax
from absl.testing import parameterized
from chex._src import fake
from imgx.model.basic import sinusoidal_positional_embedding
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
def setUpModule() -> None: # pylint: disable=invalid-name
"""Fak... | 1,478 | 27.442308 | 78 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_diffusion_gaussian.py | """Test Gaussian diffusion related classes and functions."""
from typing import Tuple
import chex
import haiku as hk
import jax
import jax.numpy as jnp
from absl.testing import parameterized
from chex._src import fake
from imgx.diffusion.gaussian_diffusion import (
DiffusionBetaSchedule,
DiffusionModelOutputT... | 19,693 | 33.250435 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_loss_cross_entropy.py | """Test dice loss functions."""
import chex
import jax
import numpy as np
from absl.testing import parameterized
from chex._src import fake
from imgx.loss import mean_cross_entropy, mean_focal_loss
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
def setUpModule() -> None: # pylint: disable=invalid-name... | 5,017 | 27.511364 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_train_state.py | """Test TrainState and related functions."""
from pathlib import Path
from typing import Dict
import chex
import jax.numpy as jnp
import jax.random
import jmp
import pytest
from chex._src import fake
from imgx.device import broadcast_to_local_devices
from imgx.exp import train_state
def setUpModule() -> None: # p... | 3,895 | 30.934426 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_exp_model.py | """Test mixed precision related functions in factory."""
import haiku as hk
import pytest
from omegaconf import DictConfig
from imgx.exp.model import build_vision_model
from imgx.model import MODEL_CLS_NAME_TO_CONFIG_NAME, SUPPORTED_VISION_MODELS
DUMMY_TASK_CONFIG = {
"name": "segmentation",
"diffusion": {
... | 1,733 | 24.5 | 77 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_dataset_augmentation.py | """Test function for data augmentation."""
from typing import Tuple
import chex
import jax
import jax.numpy as jnp
import numpy as np
from absl.testing import parameterized
from chex._src import fake
from imgx import IMAGE, LABEL
from imgx.datasets import FOREGROUND_RANGE
from imgx.datasets.augmentation import (
... | 23,132 | 29.081925 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_loss_dice.py | """Test dice loss functions."""
import chex
import jax
import numpy as np
from absl.testing import parameterized
from chex._src import fake
from imgx.loss import mean_dice_loss
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
def setUpModule() -> None: # pylint: disable=invalid-name
"""Fake multi-de... | 5,992 | 29.42132 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_diffusion_variance_schedule.py | """Test Gaussian diffusion related classes and functions."""
import chex
import jax.numpy as jnp
from absl.testing import parameterized
from chex._src import fake
from imgx.diffusion.variance_schedule import (
DiffusionBetaSchedule,
downsample_beta_schedule,
get_beta_schedule,
)
# Set `FLAGS.chex_n_cpu... | 2,208 | 27.320513 | 60 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_exp_mixed_precision.py | """Test mixed precision related functions in factory."""
import haiku as hk
import pytest
from imgx import model
from imgx.exp.mixed_precision import set_mixed_precision_policy
from imgx.model import MODEL_CLS_NAME_TO_CONFIG_NAME
from imgx.model import __all__ as all_model_classes
@pytest.mark.parametrize(
"mode... | 938 | 31.37931 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_metric_surface_distance.py | """Test loss functions."""
from functools import partial
from typing import Callable, List, Tuple, Union
import chex
import jax
import numpy as np
from absl.testing import parameterized
from imgx.metric.surface_distance import (
aggregated_surface_distance,
average_surface_distance,
get_binary_mask_bound... | 31,405 | 31.444215 | 88 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_metric_dice.py | """Test dice score metric related functions."""
import chex
import jax
import numpy as np
from absl.testing import parameterized
from chex._src import fake
from imgx.metric import dice_score, iou
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
def setUpModule() -> None: # pylint: disable=invalid-name
... | 4,360 | 25.430303 | 77 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_model_unet_3d_time.py | """Test Unet related classes and functions."""
from typing import Tuple
import chex
import haiku as hk
import jax
import jax.numpy as jnp
from absl.testing import parameterized
from chex._src import fake
from imgx.model import Unet3dSliceTime, Unet3dTime
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
d... | 6,305 | 27.278027 | 80 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_exp_eval.py | """Test functions in imgx.exp.eval."""
import chex
import jax
import numpy as np
from chex._src import fake
from imgx.exp.eval import (
get_jit_segmentation_metrics,
get_non_jit_segmentation_metrics,
)
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
def setUpModule() -> None: # pylint: disable... | 1,741 | 29.561404 | 75 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/unit/test_model_unet_3d.py | """Test Unet related classes and functions."""
from typing import Tuple
import chex
import haiku as hk
import jax
import jax.numpy as jnp
from absl.testing import parameterized
from chex._src import fake
from imgx.model import Unet3d, Unet3dSlice
# Set `FLAGS.chex_n_cpu_devices` CPU devices for all tests.
def setUp... | 5,355 | 25.646766 | 79 | py |
ImgX-DiffSeg | ImgX-DiffSeg-main/tests/data/test_dataset_iterator.py | """Test image data iterators."""
from typing import Tuple
import chex
import haiku as hk
import jax
import numpy as np
import SimpleITK as sitk # noqa: N813
from absl.testing import parameterized
from chex._src import fake
from omegaconf import DictConfig
from imgx import IMAGE, LABEL, UID
from imgx.datasets import ... | 7,123 | 29.444444 | 78 | py |
CPM-Live | CPM-Live-master/cpm-live/cpmbee_translator.py | from typing import Dict
from cpm_live.generation.bee import CPMBeeBeamSearch
from cpm_live.models import CPMBeeTorch, CPMBeeConfig
from cpm_live.tokenizers import CPMBeeTokenizer
import torch
import spacy
import re
def is_chinese(ch: str):
if "\u4e00" <= ch <= "\u9fff":
return True
return False
def ... | 6,854 | 32.768473 | 180 | py |
CPM-Live | CPM-Live-master/cpm-live/setup.py | from setuptools import setup, find_packages
setup(
name="cpm_live",
version="0.1.0",
author="OpenBMB",
author_email="openbmb@gmail.com",
description="Toolkit for CPM-Live",
packages=find_packages(),
install_requires=[
"numpy",
"torch>=1.10",
"bmtrain>=0.1.8",
... | 452 | 20.571429 | 48 | py |
CPM-Live | CPM-Live-master/cpm-live/pretrain_cpm_bee.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 15,523 | 38.805128 | 99 | py |
CPM-Live | CPM-Live-master/cpm-live/finetune_cpm_bee.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 16,454 | 37.900709 | 99 | py |
CPM-Live | CPM-Live-master/cpm-live/text_generation.py | from cpm_live.generation.bee import CPMBeeBeamSearch
from cpm_live.models import CPMBeeTorch, CPMBeeConfig
from cpm_live.tokenizers import CPMBeeTokenizer
import torch
if __name__ == "__main__":
data_list = [
{"document": "今天天气是真的<mask_0>", "<ans>": {"<mask_0>": ""}},
]
config = CPMBeeConfig.from... | 778 | 26.821429 | 71 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/dataset/distributed_dataset.py | # coding=utf-8
# Copyright 2020 The OpenBMB team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 25,959 | 32.758127 | 131 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/models/bee.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 11,433 | 38.157534 | 100 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/models/ant.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 7,842 | 35.47907 | 96 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/models/bee_torch.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 9,873 | 39.970954 | 100 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/models/__init__.py | from .ant import CPMAntConfig, CPMAnt
from .bee import CPMBeeConfig, CPMBee
from .ant_torch import CPMAntTorch
from .bee_torch import CPMBeeTorch
| 146 | 28.4 | 37 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/models/ant_torch.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 6,552 | 37.547059 | 96 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/training_tasks/ant/pretrain.py | # coding=utf-8
# Copyright 2020 The OpenBMB team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 4,499 | 37.135593 | 99 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/training_tasks/bee/pretrain.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 38,408 | 35.860845 | 100 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/embedding.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 4,165 | 36.531532 | 151 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/position_embedding.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 8,848 | 34.681452 | 100 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/feedforward.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 3,676 | 29.38843 | 176 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/layernorm.py | import torch
@torch.jit.script # type: ignore
def rms_layernorm(hidden: torch.Tensor, weight: torch.Tensor, eps: float):
old_dtype = hidden.dtype
variance = hidden.to(torch.float32).pow(2).mean(dim=-1, keepdim=True)
hidden = (hidden * torch.rsqrt(variance + eps)).to(old_dtype)
return hidden * weight
... | 1,156 | 29.447368 | 122 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/linear.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 1,721 | 32.115385 | 109 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/transformer.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 4,852 | 37.515873 | 155 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/attention.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 4,604 | 38.025424 | 191 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/native_layers/blocks.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 8,723 | 34.036145 | 198 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/embedding.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 4,458 | 36.788136 | 151 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/position_embedding.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 9,197 | 35.070588 | 100 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/feedforward.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 3,770 | 29.658537 | 176 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/layernorm.py | import torch
import bmtrain as bmt
@torch.jit.script # type: ignore
def rms_layernorm(hidden: torch.Tensor, weight: torch.Tensor, eps: float):
old_dtype = hidden.dtype
variance = hidden.to(torch.float32).pow(2).mean(dim=-1, keepdim=True)
hidden = (hidden * torch.rsqrt(variance + eps)).to(old_dtype)
r... | 1,180 | 29.282051 | 122 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/linear.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 1,901 | 31.793103 | 109 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/transformer.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 4,948 | 37.664063 | 155 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/attention.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 4,800 | 38.677686 | 191 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/layers/blocks.py | # coding=utf-8
# Copyright 2022 The OpenBMB team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or a... | 8,751 | 34.008 | 198 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/utils/export.py | import os
import time
import functools
import torch
import bmtrain as bmt
import json
from cpm_live.models import CPMBee
from .log import logger
from typing import List, Optional
def rename_if_exists(file_path):
if not os.path.exists(file_path):
return
timestamp = time.strftime('%Y%m%d%H%M%S')
fil... | 1,820 | 30.947368 | 95 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/utils/object.py | import bmtrain as bmt
import pickle
import torch
def allgather_objects(obj):
if bmt.world_size() == 1:
return [obj]
with torch.no_grad():
data_bytes: bytes = pickle.dumps(obj)
data_length: int = len(data_bytes)
gpu_data_length = torch.tensor([data_length], device="cuda", dtyp... | 994 | 33.310345 | 88 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/utils/data_utils.py | import torch
def pad(orig_items, key, padding_value=0, padding_side="left"):
items = []
if isinstance(orig_items[0][key], list):
assert isinstance(orig_items[0][key][0], torch.Tensor)
for it in orig_items:
for tr in it[key]:
items.append({key: tr})
else:
... | 1,550 | 33.466667 | 94 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/utils/gradient_shrink.py | import torch
class OpGradientShrink(torch.autograd.Function):
@staticmethod
def forward(ctx, x: torch.Tensor, alpha: float):
ctx.alpha = alpha
return x
@staticmethod
def backward(ctx, grad_output):
return grad_output * ctx.alpha, None
def gradient_shrink(x: torch.Tensor, alp... | 382 | 21.529412 | 57 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/generation/bee.py | from typing import Any, Dict, List, Tuple
import numpy as np
import torch
import torch.nn.functional as F
from .generation_utils import BeamHypotheses, apply_repetition_penalty
from ..tokenizers.bee import CPMBeeTokenizer
from ..models.bee import CPMBee
from ..training_tasks.bee.pretrain import convert_data_to_id
from ... | 26,159 | 40.52381 | 148 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/generation/ant.py | import torch
import torch.nn.functional as F
from .generation_utils import BeamHypotheses, apply_repetition_penalty, top_k_top_p_filtering
from ..utils import pad
class CPMAntGeneration:
def __init__(self, model, tokenizer, prompt_length=32):
model.eval()
self.model = model
self.tokenizer ... | 14,654 | 36.966321 | 148 | py |
CPM-Live | CPM-Live-master/cpm-live/cpm_live/generation/generation_utils.py | import torch
import torch.nn.functional as F
def top_k_top_p_filtering(logits, top_k=0, top_p=0.0, filter_value=-float("inf")):
# This function has been mostly taken from huggingface conversational ai code at
# https://medium.com/huggingface/how-to-build-a-state-of-the-art-conversational-ai-with-transfer-lear... | 4,382 | 37.787611 | 122 | py |
LOSTIN | LOSTIN-main/GNN-supernode/inference.py | import torch
from torch_geometric.data import DataLoader
import torch.optim as optim
import torch.nn.functional as F
from gnn import GNN
from torch.optim.lr_scheduler import ReduceLROnPlateau
from torch_geometric.utils import degree
from tqdm import tqdm
import argparse
import time
import numpy as np
import json
impor... | 7,700 | 43.514451 | 183 | py |
LOSTIN | LOSTIN-main/GNN-supernode/node_encoder.py | import torch
from features import get_node_feature_dims, get_edge_feature_dims
full_node_feature_dims = get_node_feature_dims()
full_edge_feature_dims = get_edge_feature_dims()
class NodeEncoder(torch.nn.Module):
def __init__(self, emb_dim):
super(NodeEncoder, self).__init__()
self.node... | 1,815 | 28.770492 | 90 | py |
LOSTIN | LOSTIN-main/GNN-supernode/test_evaluation.py | import torch
from torch_geometric.loader import DataLoader
from torch.utils.data import TensorDataset
import torch.optim as optim
import torch.nn.functional as F
from gnn import GNN
from torch.optim.lr_scheduler import ReduceLROnPlateau
from tqdm import tqdm
import argparse
import time
import numpy as np
import json
i... | 7,667 | 40.225806 | 183 | py |
LOSTIN | LOSTIN-main/GNN-supernode/evaluate.py | from sklearn.metrics import roc_auc_score, average_precision_score
import pandas as pd
import os
import numpy as np
try:
import torch
except ImportError:
torch = None
### Evaluator for graph classification
class Evaluator:
def __init__(self, name):
self.name = name
meta_info = pd.read_csv... | 14,336 | 40.677326 | 222 | py |
LOSTIN | LOSTIN-main/GNN-supernode/read_graph_pyg.py | import pandas as pd
import torch
from torch_geometric.data import Data
import os.path as osp
import numpy as np
from read_graph_raw import read_csv_graph_raw
from tqdm import tqdm
def read_graph_pyg(raw_dir, add_inverse_edge = False, additional_node_files = [], additional_edge_files = [], binary = False):
graph_l... | 1,697 | 29.321429 | 185 | py |
LOSTIN | LOSTIN-main/GNN-supernode/main_gnn.py | import torch
from torch_geometric.loader import DataLoader
import torch.optim as optim
import torch.nn.functional as F
from gnn import GNN
from torch.optim.lr_scheduler import ReduceLROnPlateau
from tqdm import tqdm
import argparse
import time
import numpy as np
import json
import operator
from functools import reduce... | 9,703 | 41.375546 | 183 | py |
LOSTIN | LOSTIN-main/GNN-supernode/gnn.py | import torch
from torch_geometric.nn import MessagePassing,BatchNorm
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
import torch.nn.functional as F
from torch_geometric.nn.inits import uniform
from torch.nn import Sequential, ReLU, Linear, ModuleList
from co... | 3,673 | 39.822222 | 188 | py |
LOSTIN | LOSTIN-main/GNN-supernode/conv.py | import torch
from torch_geometric.nn import MessagePassing
import torch.nn.functional as F
from torch_geometric.nn import global_mean_pool, global_add_pool
from node_encoder import NodeEncoder,EdgeEncoder
from torch_geometric.utils import degree
import math
### GIN convolution along the graph structure
class GINConv(... | 8,910 | 35.520492 | 182 | py |
LOSTIN | LOSTIN-main/GNN-supernode/dataset_pyg.py | from torch_geometric.data import InMemoryDataset
import pandas as pd
import shutil, os
import os.path as osp
import torch
import numpy as np
from read_graph_pyg import read_graph_pyg
class PygGraphPropPredDataset(InMemoryDataset):
def __init__(self, name, root = 'dataset', transform=None, pre_transform = None, me... | 6,385 | 41.291391 | 212 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/main_gnn_customized_delay.py | ### Libraries
import numpy as np
import argparse
from tqdm import tqdm
import matplotlib.pyplot as plts
import pandas as pd
import torch
# Preliminaries
# torchtext 0.6.0
from torchtext.data import Field, TabularDataset, BucketIterator
# Models
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence... | 9,155 | 36.679012 | 148 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/node_encoder.py | import torch
from features import get_node_feature_dims, get_edge_feature_dims
full_node_feature_dims = get_node_feature_dims()
full_edge_feature_dims = get_edge_feature_dims()
class NodeEncoder(torch.nn.Module):
def __init__(self, emb_dim):
super(NodeEncoder, self).__init__()
self.node... | 1,857 | 28.967742 | 90 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/read_graph_pyg.py | import pandas as pd
import torch
from torch_geometric.data import Data
import os.path as osp
import numpy as np
from read_graph_raw import read_csv_graph_raw
from tqdm import tqdm
def read_graph_pyg(raw_dir, add_inverse_edge = False, additional_node_files = [], additional_edge_files = [], binary = False):
graph_l... | 1,387 | 27.916667 | 156 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/main_gnn_customized_inference.py | ### Libraries
# torchtext 0.6.0
import numpy as np
import argparse
from tqdm import tqdm
# Libraries
import matplotlib.pyplot as plts
import pandas as pd
import torch
# Preliminaries
from torchtext.data import Field, TabularDataset, BucketIterator
# Models
import torch.nn as nn
from torch.nn.utils.rnn import pack_pad... | 6,775 | 37.942529 | 169 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/gnn.py | import torch
from torch_geometric.nn import MessagePassing,BatchNorm
from torch_geometric.nn import global_add_pool, global_mean_pool, global_max_pool, GlobalAttention, Set2Set
import torch.nn.functional as F
from torch_geometric.nn.inits import uniform
from torch.nn import Sequential, ReLU, Linear, ModuleList
from co... | 2,744 | 36.60274 | 188 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/conv.py | import torch
from torch_geometric.nn import MessagePassing
import torch.nn.functional as F
from torch_geometric.nn import global_mean_pool, global_add_pool
from node_encoder import NodeEncoder,EdgeEncoder
from torch_geometric.utils import degree
import math
### GIN convolution along the graph structure
class GINConv(... | 8,791 | 35.481328 | 182 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/main_gnn_customized_area.py | ### Libraries
import numpy as np
import argparse
from tqdm import tqdm
import matplotlib.pyplot as plts
import pandas as pd
import torch
# Preliminaries
# torchtext 0.6.0
from torchtext.data import Field, TabularDataset, BucketIterator
# Models
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence... | 9,153 | 36.670782 | 148 | py |
LOSTIN | LOSTIN-main/GNN-LSTM/dataset_pyg.py | from torch_geometric.data import InMemoryDataset
import pandas as pd
import shutil, os
import os.path as osp
import torch
import numpy as np
from read_graph_pyg import read_graph_pyg
class PygGraphPropPredDataset(InMemoryDataset):
def __init__(self, name, root = 'dataset', transform=None, pre_transform = None, me... | 6,691 | 38.364706 | 199 | py |
LOSTIN | LOSTIN-main/LSTM/LSTM_inference.py | ### Libraries
# torchtext 0.6.0
import numpy as np
import argparse
from tqdm import tqdm
# Libraries
import matplotlib.pyplot as plts
import pandas as pd
import torch
# Preliminaries
from torchtext.data import Field, TabularDataset, BucketIterator
# Models
import torch.nn as nn
from torch.nn.utils.rnn import pack_pad... | 6,857 | 33.29 | 149 | py |
LOSTIN | LOSTIN-main/LSTM/LSTM_area.py | ### Libraries
# torchtext 0.6.0
import numpy as np
import argparse
from tqdm import tqdm
# Libraries
import matplotlib.pyplot as plts
import pandas as pd
import torch
# Preliminaries
from torchtext.data import Field, TabularDataset, BucketIterator
# Models
import torch.nn as nn
from torch.nn.utils.rnn import pack_pad... | 9,043 | 34.328125 | 148 | py |
LOSTIN | LOSTIN-main/LSTM/LSTM_delay.py | ### Libraries
# torchtext 0.6.0
import numpy as np
import argparse
from tqdm import tqdm
# Libraries
import matplotlib.pyplot as plts
import pandas as pd
import torch
# Preliminaries
from torchtext.data import Field, TabularDataset, BucketIterator
# Models
import torch.nn as nn
from torch.nn.utils.rnn import pack_pad... | 9,049 | 34.490196 | 148 | py |
LOSTIN | LOSTIN-main/CNN/cnn_data_gen.py | import utils
import pandas as pd
import numpy as np
import argparse
import pprint as pp
from os import listdir
from os.path import isfile, join
import torch
from torch.utils.data import TensorDataset, DataLoader
def main(args):
ff_10 = pd.read_csv('flow_10.csv',header=None)
ff_15 = pd.read_csv('flow_15.csv... | 7,046 | 33.208738 | 116 | py |
LOSTIN | LOSTIN-main/CNN/train_cnn.py | import torch
from torch.autograd import Variable
import torch.nn.functional as F
import torch.nn as nn
import torch.utils.data as Data
from torch.utils.data import TensorDataset, DataLoader
import numpy as np
import argparse
# Keras -> PyTorch Implementation
# Modification: Classification -> Regression
class CNN_Reg... | 5,484 | 31.264706 | 110 | py |
scalene | scalene-master/test/testpyt.py | # -*- coding: utf-8 -*-
import random
import torch
class DynamicNet(torch.nn.Module):
def __init__(self, D_in, H, D_out):
"""
In the constructor we construct three nn.Linear instances that we will use
in the forward pass.
"""
super(DynamicNet, self).__init__()
self.... | 2,339 | 34.454545 | 85 | py |
scalene | scalene-master/test/torchtest.py | import torch
import math
def torchtest():
dtype = torch.float
#device = torch.device("cpu")
device = torch.device("cuda:0") # Uncomment this to run on GPU
# device = torch.device("cuda") # Uncomment this to run on GPU
# Create Tensors to hold input and outputs.
# By default, requires_grad=Fa... | 2,736 | 41.765625 | 85 | py |
scalene | scalene-master/test/testtf.py | import tensorflow as tf
from time import perf_counter
def config():
num_threads = 16
tf.config.threading.set_inter_op_parallelism_threads(
num_threads
)
tf.config.threading.set_intra_op_parallelism_threads(
num_threads
)
def run_benchmark():
mnist = tf.keras.datasets.mnist
... | 1,116 | 26.925 | 77 | py |
XFL | XFL-master/python/common/evaluation/metrics.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 20,407 | 37.946565 | 115 | py |
XFL | XFL-master/python/common/crypto/one_time_pad/one_time_add.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 7,887 | 40.298429 | 128 | py |
XFL | XFL-master/python/common/crypto/one_time_pad/component.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | 7,684 | 33.931818 | 125 | py |
XFL | XFL-master/python/common/dataset/azpro_data.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 5,809 | 38.52381 | 110 | py |
XFL | XFL-master/python/common/dataset/hiv.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 5,661 | 37.256757 | 110 | py |
XFL | XFL-master/python/common/dataset/sst2.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 4,360 | 36.594828 | 105 | py |
XFL | XFL-master/python/common/dataset/breast_cancer_wisconsin.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 7,461 | 40.921348 | 108 | py |
XFL | XFL-master/python/common/dataset/cifar.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 12,098 | 40.434932 | 182 | py |
XFL | XFL-master/python/common/dataset/boston_housing_price.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 5,887 | 39.054422 | 110 | py |
XFL | XFL-master/python/common/utils/model_io.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law... | 4,851 | 35.757576 | 110 | py |
XFL | XFL-master/python/common/utils/algo_utils.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | 9,180 | 30.016892 | 108 | py |
XFL | XFL-master/python/common/utils/config_checker.py | import os
import importlib
import traceback
from collections import Counter
from common.checker.compare import compare
from common.utils.logger import logger
from common.utils.config_parser import replace_variable
def find_rule_class(fed_type, operator_name, role, inference):
try:
if inference:
... | 25,081 | 35.037356 | 149 | py |
XFL | XFL-master/python/common/utils/model_preserver.py | # Copyright 2022 The XFL Authors. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable ... | 1,794 | 31.053571 | 87 | py |
XFL | XFL-master/python/common/utils/auto_descriptor/torch/torch_descriptor.py |
import inspect
import math
import torch.optim as optim
import torch.optim.lr_scheduler as lr_scheduler
import torch.nn as nn
import sklearn.metrics as sklearn_metrics
import algorithm.core.metrics as custom_metrics
from algorithm.core.metrics import metric_dict
# from common.checker.qualifiers import (OneOf, Optiona... | 20,063 | 41.780384 | 203 | py |
XFL | XFL-master/python/algorithm/config_descriptor/vertical_kmeans/label_trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
vertical_kmeans_label_trainer_rule = {
"identity": "label_trainer",
"model_info": {
"name": "vertical_kmeans"
},
"input": {
"tr... | 2,041 | 31.935484 | 109 | py |
XFL | XFL-master/python/algorithm/config_descriptor/horizontal_kmeans/assist_trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
from common.utils.auto_descriptor.torch.optimizer import optimizer
from common.utils.auto_descriptor.torch.lr_scheduler import lr_scheduler
from common.utils.aut... | 2,660 | 34.013158 | 109 | py |
XFL | XFL-master/python/algorithm/config_descriptor/horizontal_linear_regression/assist_trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
from common.utils.auto_descriptor.torch.optimizer import optimizer
from common.utils.auto_descriptor.torch.lr_scheduler import lr_scheduler
from common.utils.aut... | 3,686 | 35.50495 | 121 | py |
XFL | XFL-master/python/algorithm/config_descriptor/horizontal_logistic_regression/assist_trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
from common.utils.auto_descriptor.torch.optimizer import optimizer
from common.utils.auto_descriptor.torch.lr_scheduler import lr_scheduler
from common.utils.aut... | 4,321 | 36.912281 | 203 | py |
XFL | XFL-master/python/algorithm/config_descriptor/vertical_xgboost_infer/label_trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
vertical_xgboost_infer_label_trainer_rule = {
"identity": "label_trainer",
"model_info": {
"name": "vertical_xgboost"
},
"inference": T... | 1,197 | 26.860465 | 89 | py |
XFL | XFL-master/python/algorithm/config_descriptor/vertical_xgboost_infer/sync.py | from common.checker.x_types import String, Bool, Integer, Float, Any, All
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
vertical_xgboost_infer_sync_rule = {
"train_info": {
"train_params": {
"batch_size_val": All()
}
}
}
| 303 | 24.333333 | 89 | py |
XFL | XFL-master/python/algorithm/config_descriptor/vertical_xgboost_infer/trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
vertical_xgboost_infer_trainer_rule = {
"identity": "trainer",
"model_info": {
"name": "vertical_xgboost"
},
"inference": True,
"in... | 1,034 | 25.538462 | 89 | py |
XFL | XFL-master/python/algorithm/config_descriptor/horizontal_poisson_regression/assist_trainer.py | from common.checker.x_types import String, Bool, Integer, Float, Any
from common.checker.qualifiers import OneOf, SomeOf, RepeatableSomeOf, Required, Optional
from common.utils.auto_descriptor.torch.optimizer import optimizer
from common.utils.auto_descriptor.torch.lr_scheduler import lr_scheduler
from common.utils.aut... | 3,544 | 36.315789 | 122 | py |
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