id stringlengths 9 9 | text stringlengths 312 2.4k | title stringclasses 1
value |
|---|---|---|
000000200 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
import scipy.spatial.distance
example_array = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
import itertools
n = example_array.max()+1
in... | |
000000201 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
from scipy import interpolate
import numpy as np
x, y, x_val = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
result = np.zeros((5, 100))
for i in range(5):
... | |
000000202 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import scipy.integrate
c, low, high = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
result = scipy.integrate.quadrature(lambda x: 2*c*x, low, high)[0]
#p... | |
000000203 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
from scipy.sparse import csr_matrix
col = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
mean = col.mean()
N = col.shape[0]
sqr = col.c... | |
000000204 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import scipy.integrate
import numpy as np
N0, time_span = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def dN1_dt(t, N1):
input = 1-np.cos(t) if 0<t<2*... | |
000000205 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
import scipy.stats
p_values = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
z_scores = scipy.stats.norm.ppf(p_values)
#print(z_scores)
... | |
000000206 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
import scipy.fft as sf
N = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
result = sf.dct(np.eye(N), axis=0, norm= 'ortho')
#print(resu... | |
000000207 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
from scipy.sparse import csr_matrix
M, row, column = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
result = np.array(M[row,column]).squ... | |
000000208 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
from scipy import ndimage
img = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
threshold = 0.75
blobs = img > threshold
labels, result =... | |
000000209 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
from scipy.sparse import csr_matrix
M, row, column = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
result = M[row,column]
#print(result... | |
000000210 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
from scipy import sparse
import numpy as np
import math
sa = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
sa = sparse.csc_matrix(sa.toarray() / np.sqrt(np.... | |
000000211 |
import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import numpy as np
from scipy.linalg import block_diag
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
result = block_diag(*a)
#print(result)
with open(... | |
000000212 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths_transposed = tf.expand_dims(l... | |
000000213 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.expand_dims(a, 2)
r... | |
000000214 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths = [8-x for x in lengths]
... | |
000000215 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
x.assign(114514)
###END SOLUTION
result = x
with open('result/... | |
000000216 | import pickle
import argparse
import shutil
import os
if os.path.exists('my_model'):
shutil.rmtree('my_model')
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflo... | |
000000217 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(labels):
### BEGIN SOLUTION
result = tf.one_hot(indices=label... | |
000000218 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(A):
return tf.reduce_sum(A, 1)
re... | |
000000219 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.squeeze(a)
result =... | |
000000220 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.expand_dims(tf.expan... | |
000000221 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
input = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
tf.compat.v1.disable_eager_execution()
###BEGIN SOLUTION
def g(input):
ds... | |
000000222 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x):
return [tf.compat.as_str_any(a) for a in x]
resu... | |
000000223 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a,b):
return tf.reduce_sum(tf.square( tf.subtract( ... | |
000000224 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.argmin(a,axis=0)
result = g(a.__copy__... | |
000000225 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
FLAG = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
result = tf.version.VERSION
###END SOLUTION
with open('resu... | |
000000226 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(lengths):
### BEGIN SOLUTION
lengths_transposed = tf.expand_d... | |
000000227 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x):
non_zero = tf.cast(x != 0, tf.float32)
y = tf... | |
000000228 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(A):
return tf.reduce_prod(A, 1)
r... | |
000000229 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
x.assign(1)
###END SOLUTION
result = x
with open('result/resul... | |
000000230 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
FLAG = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
tf.random.set_seed(10)
def get_values():
A = tf.random.nor... | |
000000231 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.argmax(a,axis=0)
result = g(a.__copy__... | |
000000232 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
return tf.one_hot(indices=labels, depth... | |
000000233 | import pickle
import argparse
import numpy as np
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
A = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(A):
return tf.math.reciprocal(A)
... | |
000000234 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
seed_x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(seed_x):
### BEGIN SOLUTION
tf.random.set_seed(seed_x)
res... | |
000000235 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a,b):
return tf.reduce_sum(tf.square( tf.subtract( ... | |
000000236 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a,b):
tile_a = tf.tile(tf.expand_dims(a, 1), [1, tf... | |
000000237 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
t = tf.one_hot(indices=labels, depth=10... | |
000000238 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(x):
### BEGIN SOLUTION
result = [tf.compat.as_str_any(a) for a in x... | |
000000239 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x):
non_zero = tf.cast(x != 0, tf.float32)
y = tf... | |
000000240 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
seed_x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(seed_x):
tf.random.set_seed(seed_x)
return t... | |
000000241 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A,B = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
import numpy as np
def g(A,B):
return ... | |
000000242 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.argmax(a,axis=1)
result = g(a.__copy__... | |
000000243 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
A,B = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(A,B):
### BEGIN SOLUTION
result = tf.reduce_sum(tf.square( tf.sub... | |
000000244 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths_transposed = tf.expand_dims(l... | |
000000245 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x,y,z = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(x,y,z):
### BEGIN SOLUTION
result = tf.gather_nd(x, [y, z])
... | |
000000246 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A,B = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
import numpy as np
def g(A,B):
return ... | |
000000247 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths = [8-x for x in lengths]
... | |
000000248 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
t = tf.one_hot(indices=labels, depth=10... | |
000000249 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x,y,z = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x,y,z):
return tf.gather_nd(x, [y, z])
result = ... | |
000000250 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(a,b):
### BEGIN SOLUTION
tile_a = tf.tile(tf.expand_dims(a, 1), [... | |
000000251 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
return tf.one_hot(indices=labels, depth... | |
000000252 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(a):
### BEGIN SOLUTION
result = tf.argmax(a,axis=1)
### END SO... | |
000000253 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
seed_x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(seed_x):
tf.random.set_seed(seed_x)
return t... | |
000000254 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(x):
### BEGIN SOLUTION
non_zero = tf.cast(x != 0, tf.float32)
y... | |
000000255 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
input = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
tf.compat.v1.disable_eager_execution()
def f(input):
### BEGIN SOLUTION
... | |
000000256 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x,row,col = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x,row,col):
index = [[row[i],col[i]] for i in... | |
000000257 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths_transposed = tf.expand_dims(l... | |
000000258 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.expand_dims(a, 2)
r... | |
000000259 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths = [8-x for x in lengths]
... | |
000000260 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
x.assign(114514)
###END SOLUTION
result = x
with open('result/... | |
000000261 | import pickle
import argparse
import shutil
import os
if os.path.exists('my_model'):
shutil.rmtree('my_model')
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflo... | |
000000262 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(labels):
### BEGIN SOLUTION
result = tf.one_hot(indices=label... | |
000000263 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(A):
return tf.reduce_sum(A, 1)
re... | |
000000264 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.squeeze(a)
result =... | |
000000265 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.expand_dims(tf.expan... | |
000000266 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
input = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
tf.compat.v1.disable_eager_execution()
###BEGIN SOLUTION
def g(input):
ds... | |
000000267 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x):
return [tf.compat.as_str_any(a) for a in x]
resu... | |
000000268 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a,b):
return tf.reduce_sum(tf.square( tf.subtract( ... | |
000000269 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.argmin(a,axis=0)
result = g(a.__copy__... | |
000000270 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
FLAG = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
result = tf.version.VERSION
###END SOLUTION
with open('resu... | |
000000271 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(lengths):
### BEGIN SOLUTION
lengths_transposed = tf.expand_d... | |
000000272 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x):
non_zero = tf.cast(x != 0, tf.float32)
y = tf... | |
000000273 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(A):
return tf.reduce_prod(A, 1)
r... | |
000000274 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
x.assign(1)
###END SOLUTION
result = x
with open('result/resul... | |
000000275 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
FLAG = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
tf.random.set_seed(10)
def get_values():
A = tf.random.nor... | |
000000276 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.argmax(a,axis=0)
result = g(a.__copy__... | |
000000277 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
return tf.one_hot(indices=labels, depth... | |
000000278 | import pickle
import argparse
import numpy as np
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
A = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(A):
return tf.math.reciprocal(A)
... | |
000000279 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
seed_x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(seed_x):
### BEGIN SOLUTION
tf.random.set_seed(seed_x)
res... | |
000000280 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a,b):
return tf.reduce_sum(tf.square( tf.subtract( ... | |
000000281 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a,b):
tile_a = tf.tile(tf.expand_dims(a, 1), [1, tf... | |
000000282 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
t = tf.one_hot(indices=labels, depth=10... | |
000000283 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(x):
### BEGIN SOLUTION
result = [tf.compat.as_str_any(a) for a in x... | |
000000284 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x):
non_zero = tf.cast(x != 0, tf.float32)
y = tf... | |
000000285 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
seed_x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(seed_x):
tf.random.set_seed(seed_x)
return t... | |
000000286 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A,B = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
import numpy as np
def g(A,B):
return ... | |
000000287 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(a):
return tf.argmax(a,axis=1)
result = g(a.__copy__... | |
000000288 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
A,B = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(A,B):
### BEGIN SOLUTION
result = tf.reduce_sum(tf.square( tf.sub... | |
000000289 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths_transposed = tf.expand_dims(l... | |
000000290 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x,y,z = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(x,y,z):
### BEGIN SOLUTION
result = tf.gather_nd(x, [y, z])
... | |
000000291 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
import numpy as np
A,B = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
import numpy as np
def g(A,B):
return ... | |
000000292 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
lengths = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(lengths):
lengths = [8-x for x in lengths]
... | |
000000293 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
t = tf.one_hot(indices=labels, depth=10... | |
000000294 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x,y,z = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(x,y,z):
return tf.gather_nd(x, [y, z])
result = ... | |
000000295 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a,b = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(a,b):
### BEGIN SOLUTION
tile_a = tf.tile(tf.expand_dims(a, 1), [... | |
000000296 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
labels = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(labels):
return tf.one_hot(indices=labels, depth... | |
000000297 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
a = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(a):
### BEGIN SOLUTION
result = tf.argmax(a,axis=1)
return res... | |
000000298 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
seed_x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
###BEGIN SOLUTION
def g(seed_x):
tf.random.set_seed(seed_x)
return t... | |
000000299 | import pickle
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--test_case", type=int, default=1)
args = parser.parse_args()
import tensorflow as tf
x = pickle.load(open(f"input/input{args.test_case}.pkl", "rb"))
def f(x):
### BEGIN SOLUTION
non_zero = tf.cast(x != 0, tf.float32)
y... |
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