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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pytorch | pytorch-main/caffe2/python/operator_test/pad_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import unittest
class TestPad(serial.SerializedTestCase):
@serial.given(pad_t=st.integers(-5, 0),
... | 1,377 | 26.56 | 73 | py |
pytorch | pytorch-main/caffe2/python/operator_test/reduce_ops_test.py |
from caffe2.python import core, workspace
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import itertools as it
class TestReduceOps(serial.SerializedT... | 17,341 | 37.537778 | 100 | py |
pytorch | pytorch-main/caffe2/python/operator_test/top_k_test.py |
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
class TestTopK(serial.SerializedTestCase):
def top_k_ref(self, X, k... | 9,113 | 35.898785 | 78 | py |
pytorch | pytorch-main/caffe2/python/operator_test/layer_norm_op_test.py |
from caffe2.python import brew, core, workspace
from caffe2.python.model_helper import ModelHelper
from functools import partial
from hypothesis import given, settings
from typing import Optional, Tuple
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as se... | 14,782 | 35.056098 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/ensure_clipped_test.py |
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
import numpy.testing as npt
from caffe2.python import core, workspace
from hypothesis import given
class TestEnsureClipped(hu.HypothesisTestCase):
@given(
X=hu.arrays(dims=[5, 10], elements=hu.floats(mi... | 1,505 | 33.227273 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/thresholded_relu_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import hypothesis.strategies as st
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import numpy as np
import unittest
class TestThresholdedRelu(serial.SerializedTestCase):
... | 2,323 | 30.405405 | 68 | py |
pytorch | pytorch-main/caffe2/python/operator_test/assert_test.py |
import numpy as np
from hypothesis import given, settings
import hypothesis.strategies as st
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
class TestAssert(hu.HypothesisTestCase):
@given(
dtype=st.sampled_from(['bool_', 'int32', 'int64']),
shape=st.lists(elemen... | 797 | 25.6 | 76 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rowwise_counter_test.py |
import unittest
import caffe2.python.hypothesis_test_util as hu
import numpy as np
from caffe2.python import core, workspace
def update_counter_ref(prev_iter, update_counter, indices, curr_iter, counter_halflife):
prev_iter_out = prev_iter.copy()
update_counter_out = update_counter.copy()
counter_neg_... | 2,205 | 30.514286 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/stats_ops_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
class TestCounterOps(TestCase):
def test_stats_ops(self):
# The global StatRegistry isn't reset when the workspace is reset,
# so there may be existing stats from a previous test
... | 1,789 | 33.423077 | 74 | py |
pytorch | pytorch-main/caffe2/python/operator_test/normalize_op_test.py |
import functools
import numpy as np
from hypothesis import given, settings
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import copy
class TestNormalizeOp(hu.HypothesisTestCase):
@given(
X=hu.tensor(
min_dim=1, max_dim=5, elements=hu.floats(min_value=0.5, ... | 1,679 | 29.545455 | 86 | py |
pytorch | pytorch-main/caffe2/python/operator_test/prepend_dim_test.py |
import numpy as np
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
from caffe2.proto import caffe2_pb2
class TestPrependDim(TestCase):
def _test_fwd_bwd(self):
old_shape = (128, 2, 4)
new_shape = (8, 16, 2, 4)
X = np.random.rand(*old_shape).astyp... | 1,505 | 27.961538 | 73 | py |
pytorch | pytorch-main/caffe2/python/operator_test/mod_op_test.py | import numpy
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
@st.composite
def _data(draw):
return draw(
hu.tensor(
dtype=np.int64,
elements=st.integers(
... | 1,459 | 22.548387 | 82 | py |
pytorch | pytorch-main/caffe2/python/operator_test/group_norm_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
import unittest
class TestGroupNormOp(serial.SerializedTestCase):
de... | 5,252 | 33.11039 | 77 | py |
pytorch | pytorch-main/caffe2/python/operator_test/lengths_reducer_fused_nbit_rowwise_ops_test.py |
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core, workspace
from hypothesis import given
class TestLengthsReducerOpsFusedNBitRowwise(hu.HypothesisTestCase):
@given(
num_rows=st.integers(1, 20),
blocksize=st.sampl... | 15,495 | 37.167488 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/ensure_cpu_output_op_test.py |
from hypothesis import given
import numpy as np
import hypothesis.strategies as st
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
@st.composite
def _dev_options(draw):
op_dev = draw(st.sampled_from(hu.device_options))
if op_dev == hu.cpu_do:
# the CPU o... | 1,244 | 22.942308 | 65 | py |
pytorch | pytorch-main/caffe2/python/operator_test/expand_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestExpandOp(serial.SerializedTestCase):
def _rand_shape(self,... | 2,109 | 30.969697 | 67 | py |
pytorch | pytorch-main/caffe2/python/operator_test/spatial_bn_op_test.py |
from caffe2.python import brew, core, utils, workspace
import caffe2.python.hip_test_util as hiputl
import caffe2.python.hypothesis_test_util as hu
from caffe2.python.model_helper import ModelHelper
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, assume, settings
... | 20,182 | 39.446894 | 79 | py |
pytorch | pytorch-main/caffe2/python/operator_test/weighted_sum_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestWeightedSumOp(serial.SerializedTestCase):
@given(
... | 3,052 | 28.931373 | 77 | py |
pytorch | pytorch-main/caffe2/python/operator_test/python_op_test.py |
from caffe2.python import core, workspace
from caffe2.python.core import CreatePythonOperator
import caffe2.python.hypothesis_test_util as hu
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
import unittest
class PythonOpTest(hu.HypothesisTestCase):
@given(x=hu.tenso... | 1,312 | 28.840909 | 74 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rnn_cell_test.py |
from caffe2.python import (
core, gradient_checker, rnn_cell, workspace, scope, utils
)
from caffe2.python.attention import AttentionType
from caffe2.python.model_helper import ModelHelper, ExtractPredictorNet
from caffe2.python.rnn.rnn_cell_test_util import sigmoid, tanh, _prepare_rnn
from caffe2.proto import... | 59,707 | 32.60045 | 84 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rmac_regions_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
class RMACRegionsOpTest(hu.HypothesisTestCase):
@given(
n=st.integers(500, 500),
h=st.integers(1, 10),
w=st.integ... | 3,178 | 30.79 | 71 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rms_norm_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
import unittest
class TestRMSNormOp(hu.HypothesisTestCase):
@given(
M=st.integers(0, 8),
N=st.integers(1, 16),
eps... | 1,325 | 26.625 | 69 | py |
pytorch | pytorch-main/caffe2/python/operator_test/flatten_op_test.py |
from hypothesis import given
import numpy as np
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
class TestFlatten(hu.HypothesisTestCase):
@given(X=hu.tensor(min_dim=2, max_dim=4),
**hu.gcs)
def test_flatten(self, X, gc, dc):
for axis in range(X.ndim + 1)... | 922 | 22.666667 | 64 | py |
pytorch | pytorch-main/caffe2/python/operator_test/gather_ranges_op_test.py |
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import numpy as np
from caffe2.python import core, workspace
from hypothesis import given, settings, strategies as st
def batched_boarders_and_data(
data_min_size=5,
data_max_size=10,
exam... | 9,125 | 31.827338 | 87 | py |
pytorch | pytorch-main/caffe2/python/operator_test/weight_scale_test.py | # Copyright (c) 2016-present, Facebook, Inc.
#
# 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 agreed... | 2,057 | 38.576923 | 116 | py |
pytorch | pytorch-main/caffe2/python/operator_test/conv_transpose_test.py |
import numpy as np
from hypothesis import assume, given, settings
import hypothesis.strategies as st
from caffe2.proto import caffe2_pb2
from caffe2.python import core, utils
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.hip_test_util as hiputl
class TestConvolutionTranspose(hu.HypothesisT... | 15,945 | 36.083721 | 77 | py |
pytorch | pytorch-main/caffe2/python/operator_test/sparse_lengths_sum_benchmark.py |
import argparse
import datetime
import numpy as np
from caffe2.python import core, workspace
DTYPES = {
"uint8": np.uint8,
"uint8_fused": np.uint8,
"float": np.float32,
"float16": np.float16,
}
def benchmark_sparse_lengths_sum(
dtype_str,
categorical_limit,
embedding_size,
average... | 4,159 | 29.814815 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/fc_operator_test.py |
from caffe2.proto import caffe2_pb2
from caffe2.python import core
from hypothesis import assume, given, settings, HealthCheck
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import unittest
... | 3,720 | 33.137615 | 83 | py |
pytorch | pytorch-main/caffe2/python/operator_test/lpnorm_op_test.py |
import numpy as np
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
from hypothesis import given, settings
import hypothesis.strategies as st
class LpnormTest(hu.HypothesisTestCase):
def _test_Lp_Norm(self, inputs, gc, dc):
X = inputs[0]
# avoid kinks ... | 3,148 | 29.872549 | 85 | py |
pytorch | pytorch-main/caffe2/python/operator_test/sinusoid_position_encoding_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import math
MAX_TEST_EMBEDDING_SIZE = 20
MAX_TEST_SEQUENCE_LENGTH = 10
MAX... | 2,308 | 30.630137 | 81 | py |
pytorch | pytorch-main/caffe2/python/operator_test/channel_stats_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
import unittest
class TestChannelStatsOp(serial.SerializedTestCase):
... | 2,639 | 29 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/margin_ranking_criterion_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
class TestMarginRankingCriterion(serial.SerializedTestCase):
@given(... | 1,816 | 32.648148 | 78 | py |
pytorch | pytorch-main/caffe2/python/operator_test/negate_gradient_op_test.py |
from caffe2.python import workspace, core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
class TestNegateGradient(serial.SerializedTestCase):
@giv... | 1,518 | 32.755556 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/given_tensor_fill_op_test.py |
from caffe2.python import core
from hypothesis import given
import hypothesis.strategies as st
import caffe2.python.hypothesis_test_util as hu
import numpy as np
import unittest
class TestGivenTensorFillOps(hu.HypothesisTestCase):
@given(X=hu.tensor(min_dim=1, max_dim=4, dtype=np.int32),
t=st.sam... | 1,503 | 30.333333 | 74 | py |
pytorch | pytorch-main/caffe2/python/operator_test/stats_put_ops_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
class TestPutOps(TestCase):
def test_default_value(self):
magnitude_expand = int(1e12)
stat_name = "stat".encode('ascii')
sum_postfix = "/stat_value/sum".encode("ascii")
c... | 6,585 | 32.602041 | 74 | py |
pytorch | pytorch-main/caffe2/python/operator_test/loss_ops_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestLossOps(serial.SerializedTestCase):
@serial.given(n=st.integers(1, 8), **hu.gcs)
def test_ave... | 902 | 20.5 | 67 | py |
pytorch | pytorch-main/caffe2/python/operator_test/wngrad_test.py |
import functools
import logging
import hypothesis
from hypothesis import given, settings, HealthCheck
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
logger =... | 8,279 | 36.808219 | 82 | py |
pytorch | pytorch-main/caffe2/python/operator_test/sparse_to_dense_mask_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
class TestFcOperator(hu.HypothesisTestCase):
@given(n=st.integers(1, 10), k=st.integers(1, 5),
use_length=st.booleans(), **hu... | 3,693 | 31.690265 | 77 | py |
pytorch | pytorch-main/caffe2/python/operator_test/clip_op_test.py |
import numpy as np
from hypothesis import given, settings
import hypothesis.strategies as st
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
class TestClip(serial.SerializedTestCase):
@given(X=hu.tensor(min_d... | 1,984 | 27.768116 | 67 | py |
pytorch | pytorch-main/caffe2/python/operator_test/ngram_ops_test.py |
import hypothesis.strategies as st
from caffe2.python import core, workspace
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import numpy as np
class TestNGramOps(hu.HypothesisTestCase):
@given(
seed=st.integers(0, 2**32 - 1),
N=st.integers(min_value=10, max_val... | 2,327 | 29.631579 | 70 | py |
pytorch | pytorch-main/caffe2/python/operator_test/sparse_dropout_with_replacement_op_test.py |
from caffe2.python import core
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import numpy as np
class SparseDropoutWithReplacementTest(hu.HypothesisTestCase):
@given(**hu.gcs_cpu_only)
def test_no_dropout(self, gc, dc):
X = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10]).... | 2,885 | 40.826087 | 74 | py |
pytorch | pytorch-main/caffe2/python/operator_test/learning_rate_adaption_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
class TestLearningRateAdaption(serial.SerializedTestCase):
@given(in... | 2,837 | 33.609756 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/deform_conv_test.py |
import unittest
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, utils, workspace
from hypothesis import assume, given
def _cudnn_supports(dilation=False, nhwc=False):
"""Return True if cuDN... | 19,276 | 30.915563 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/transpose_op_test.py |
from caffe2.python import core, workspace
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import unittest
class TestTransposeOp(serial.SerializedTestCa... | 2,722 | 31.035294 | 77 | py |
pytorch | pytorch-main/caffe2/python/operator_test/index_hash_ops_test.py |
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
from hypothesis import given, settings
import numpy as np
class TestIndexHashOps(serial.SerializedTestCase):
@given(... | 2,885 | 37.48 | 79 | py |
pytorch | pytorch-main/caffe2/python/operator_test/key_split_ops_test.py |
import hypothesis.strategies as st
from caffe2.python import core, workspace
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import numpy as np
class TestKeySplitOps(hu.HypothesisTestCase):
@given(
X=hu.arrays(
dims=[1000],
dtype=np.int64,
... | 1,289 | 27.043478 | 78 | py |
pytorch | pytorch-main/caffe2/python/operator_test/hsm_test.py |
from hypothesis import given, settings
import numpy as np
import unittest
from caffe2.proto import caffe2_pb2, hsm_pb2
from caffe2.python import workspace, core, gradient_checker
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.hsm_util as hsmu
# User inputs tree using protobuf file or, in thi... | 9,455 | 36.375494 | 79 | py |
pytorch | pytorch-main/caffe2/python/operator_test/sparse_gradient_checker_test.py |
import numpy as np
from scipy.sparse import coo_matrix
from hypothesis import given, settings
import hypothesis.strategies as st
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
class TestSparseGradient(hu.HypothesisTestCase):
@given(M=st.integers(min_value=5, max_value=20),
... | 1,294 | 25.979167 | 62 | py |
pytorch | pytorch-main/caffe2/python/operator_test/quantile_test.py |
import unittest
import caffe2.python.hypothesis_test_util as hu
import numpy as np
from caffe2.python import core, workspace
class TestQuantile(hu.HypothesisTestCase):
def _test_quantile(self, inputs, quantile, abs, tol):
net = core.Net("test_net")
net.Proto().type = "dag"
input_tensors... | 3,276 | 36.666667 | 82 | py |
pytorch | pytorch-main/caffe2/python/operator_test/lengths_pad_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestLengthsPadOp(serial.SerializedTestCase):
@serial.given(
inputs=hu.lengths_tensor(
... | 1,625 | 27.034483 | 79 | py |
pytorch | pytorch-main/caffe2/python/operator_test/recurrent_network_test.py |
from caffe2.python import recurrent, workspace
from caffe2.python.model_helper import ModelHelper
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class R... | 14,048 | 35.585938 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/video_input_op_test.py |
import os
import shutil
import sys
import tempfile
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import model_helper, workspace
try:
import lmdb
except ImportError as e:
raise unittest.SkipTest("python-lmdb is not installed") from e
class VideoInputOpTest(unitt... | 10,515 | 34.647458 | 82 | py |
pytorch | pytorch-main/caffe2/python/operator_test/trigonometric_op_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import numpy as np
import unittest
class TestTrigonometricOp(serial.SerializedTestCase):
@given(
X=hu.tensor(eleme... | 1,715 | 31.377358 | 84 | py |
pytorch | pytorch-main/caffe2/python/operator_test/sparse_ops_test.py |
from caffe2.python import core
from caffe2.python.test_util import rand_array
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
class TestScatterOps(serial... | 3,469 | 37.555556 | 110 | py |
pytorch | pytorch-main/caffe2/python/operator_test/lengths_tile_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestLengthsTileOp(serial.SerializedTestCase):
@serial.given(
inputs=st.integers(min_value=1, ... | 1,332 | 24.634615 | 75 | py |
pytorch | pytorch-main/caffe2/python/operator_test/erf_op_test.py |
import math
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import numpy as np
import unittest
class TestErfOp(serial.SerializedTestCase):
@given(
X=hu.tensor(el... | 749 | 23.193548 | 87 | py |
pytorch | pytorch-main/caffe2/python/operator_test/elementwise_op_broadcast_test.py |
import unittest
from hypothesis import given, assume, settings
import hypothesis.strategies as st
import numpy as np
import operator
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_u... | 17,462 | 39.801402 | 100 | py |
pytorch | pytorch-main/caffe2/python/operator_test/percentile_op_test.py |
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import numpy as np
class TestPercentileOp(hu.HypothesisTestCase):
def _test_percentile_op(
self,
original_inp,
value_to_pct_map,
dist_lengths,
expected_values
):
op = ... | 4,427 | 32.801527 | 88 | py |
pytorch | pytorch-main/caffe2/python/operator_test/mkl_packed_fc_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
import numpy as np
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
@unittest.skipIf(not core.IsOperator("PackedFC"),
"PackedFC is not supported in this caffe2 build.")
class PackedFCTes... | 2,647 | 33.38961 | 85 | py |
pytorch | pytorch-main/caffe2/python/operator_test/moments_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import itertools as it
import numpy as np
class TestMomentsOp(serial.SerializedTestCase):
def run_moments_test(self, X, axes, ... | 1,722 | 30.907407 | 72 | py |
pytorch | pytorch-main/caffe2/python/operator_test/instance_norm_test.py |
import numpy as np
from hypothesis import given, assume, settings
import hypothesis.strategies as st
from caffe2.python import core, model_helper, brew, utils
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import unittest
class TestInstanceNor... | 9,917 | 34.805054 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/data_couple_op_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
class TestDataCoupleOp(TestCase):
def test_data_couple_op(self):
param_array = np.random.rand(10, 10)
gradient_array = np.random.rand(10, 10)
extra_array = np.random.rand(10, 10)... | 858 | 26.709677 | 58 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rank_loss_operator_test.py |
from caffe2.python import core, workspace
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestPairWiseLossOps(serial.SerializedTestCase):
@given(X=hu.ar... | 5,752 | 37.871622 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/weighted_sample_test.py |
import numpy as np
from hypothesis import given
import hypothesis.strategies as st
from caffe2.python import core
from caffe2.python import workspace
import caffe2.python.hypothesis_test_util as hu
class TestWeightedSample(hu.HypothesisTestCase):
@given(
batch=st.integers(min_value=0, max_value=128... | 2,739 | 32.82716 | 78 | py |
pytorch | pytorch-main/caffe2/python/operator_test/boolean_mask_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from hypothesis import assume, given, settings
import hypothesis.strategies as st
import numpy as np
class TestBooleanMaskOp(serial.SerializedTestCase):
@given(x=h... | 16,389 | 39.469136 | 79 | py |
pytorch | pytorch-main/caffe2/python/operator_test/cross_entropy_ops_test.py |
from caffe2.python import core
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
import unittest
def sigmoid(x):
return 1.0 / (1.0 + np.exp(-x))
def sigmoid_cross_entropy_with_logits(x, z):
return np.maximum(x, 0) - x * z +... | 10,085 | 34.020833 | 83 | py |
pytorch | pytorch-main/caffe2/python/operator_test/bisect_percentile_op_test.py | from typing import List
import hypothesis.strategies as st
from caffe2.python import core, workspace
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import bisect
import numpy as np
class TestBisectPercentileOp(hu.HypothesisTestCase):
def compare_reference(
self,
... | 6,290 | 33.95 | 93 | py |
pytorch | pytorch-main/caffe2/python/operator_test/gru_test.py |
from caffe2.python import workspace, core, scope, gru_cell
from caffe2.python.model_helper import ModelHelper
from caffe2.python.rnn.rnn_cell_test_util import sigmoid, tanh, _prepare_rnn
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
from caffe2.... | 12,932 | 32.161538 | 83 | py |
pytorch | pytorch-main/caffe2/python/operator_test/locally_connected_op_test.py |
import numpy as np
from hypothesis import given, settings, assume
import hypothesis.strategies as st
from caffe2.python import core, utils, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
class TestLocallyConnectedOp(serial.Serialized... | 7,761 | 32.895197 | 78 | py |
pytorch | pytorch-main/caffe2/python/operator_test/elementwise_ops_test.py |
from caffe2.python import core, workspace
from hypothesis import given, assume, settings
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
import unittest
class TestElementwiseOps(hu.HypothesisTestCase):
@given(X=hu.tensor(dtype=np.float32), **hu.gcs)
... | 33,354 | 30.796949 | 92 | py |
pytorch | pytorch-main/caffe2/python/operator_test/resize_op_test.py |
import numpy as np
import hypothesis.strategies as st
import unittest
import caffe2.python.hypothesis_test_util as hu
from caffe2.python import core
from caffe2.proto import caffe2_pb2
from hypothesis import assume, given, settings
class TestResize(hu.HypothesisTestCase):
@given(height_scale=st.floats(0.25, 4... | 9,417 | 35.933333 | 87 | py |
pytorch | pytorch-main/caffe2/python/operator_test/channel_shuffle_test.py |
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core
class ChannelShuffleOpsTest(serial.SerializedTestCase):
def _channel_shuffle_nchw_ref(self, X, group):
... | 1,794 | 29.948276 | 86 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rand_quantization_op_speed_test.py |
import time
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core, workspace
from hypothesis import given, settings
np.set_printoptions(precision=6)
class TestSpeedFloatToFusedRandRowwiseQuantized(hu.HypothesisTestCase):
@given(
... | 3,128 | 29.086538 | 87 | py |
pytorch | pytorch-main/caffe2/python/operator_test/image_input_op_test.py |
import unittest
try:
import cv2
import lmdb
except ImportError:
pass # Handled below
from PIL import Image
import numpy as np
import shutil
import io
import sys
import tempfile
# TODO: This test does not test scaling because
# the algorithms used by OpenCV in the C and Python
# version seem to diffe... | 17,345 | 38.967742 | 86 | py |
pytorch | pytorch-main/caffe2/python/operator_test/dense_vector_to_id_list_op_test.py |
from caffe2.python import core
from hypothesis import given
import caffe2.python.hypothesis_test_util as hu
import hypothesis.extra.numpy as hnp
import hypothesis.strategies as st
import numpy as np
@st.composite
def id_list_batch(draw):
batch_size = draw(st.integers(2, 2))
values_dtype = np.float32
... | 2,044 | 29.522388 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/arg_ops_test.py |
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
class TestArgOps(serial.SerializedTestCase):
@given(
X=hu.te... | 1,917 | 28.96875 | 71 | py |
pytorch | pytorch-main/caffe2/python/operator_test/mul_gradient_benchmark.py |
import argparse
import numpy as np
from caffe2.python import core, workspace
def benchmark_mul_gradient(args):
workspace.FeedBlob("dC", np.random.rand(args.m, args.n).astype(np.float32))
workspace.FeedBlob("A", np.random.rand(args.m, args.n).astype(np.float32))
workspace.FeedBlob("B", np.random.rand... | 1,509 | 28.607843 | 79 | py |
pytorch | pytorch-main/caffe2/python/operator_test/atomic_ops_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import unittest
class TestAtomicOps(TestCase):
@unittest.skip("Test is flaky: https://github.com/pytorch/pytorch/issues/28179")
def test_atomic_ops(self):
"""
Test that both countdown and checksum are u... | 4,102 | 43.597826 | 84 | py |
pytorch | pytorch-main/caffe2/python/operator_test/blobs_queue_db_test.py |
import numpy as np
import caffe2.proto.caffe2_pb2 as caffe2_pb2
from caffe2.python import core, workspace, timeout_guard, test_util
class BlobsQueueDBTest(test_util.TestCase):
def test_create_blobs_queue_db_string(self):
def add_blobs(queue, num_samples):
blob = core.BlobReference("blob"... | 3,240 | 33.478723 | 78 | py |
pytorch | pytorch-main/caffe2/python/operator_test/utility_ops_test.py |
from caffe2.python import core, workspace
from hypothesis import assume, given, settings
from caffe2.proto import caffe2_pb2
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import random
clas... | 15,054 | 30.169772 | 97 | py |
pytorch | pytorch-main/caffe2/python/operator_test/crf_test.py |
from caffe2.python import workspace, crf, brew
from caffe2.python.model_helper import ModelHelper
import numpy as np
from scipy.special import logsumexp
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
from hypothesis import given, settings
class TestCRFOp(hu.HypothesisTestCase):... | 5,315 | 36.702128 | 84 | py |
pytorch | pytorch-main/caffe2/python/operator_test/bbox_transform_test.py |
from caffe2.python import core
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
# Reference implementation from detectron/lib/utils/boxes.py
def bbox_tra... | 12,258 | 33.147632 | 86 | py |
pytorch | pytorch-main/caffe2/python/operator_test/reshape_ops_test.py |
import numpy as np
from numpy.testing import assert_array_equal
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
from caffe2.proto import caffe2_pb2
class TestLengthsToShapeOps(TestCase):
def test_lengths_to_shape_ops(self):
workspace.FeedBlob('l', np.array([200,... | 8,211 | 37.735849 | 118 | py |
pytorch | pytorch-main/caffe2/python/operator_test/ceil_op_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
from hypothesis import given, settings
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import unittest
class TestCeil(serial.SerializedTestCase):
@given(X... | 888 | 21.225 | 69 | py |
pytorch | pytorch-main/caffe2/python/operator_test/jsd_ops_test.py |
from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
def entropy(p):
q = 1. - p
return -p * np.log(p) - q * np.log(q)
def jsd(p, q):
return [entropy(p ... | 1,044 | 23.880952 | 73 | py |
pytorch | pytorch-main/caffe2/python/operator_test/dataset_ops_test.py | import functools
import operator
import string
import hypothesis.strategies as st
import numpy as np
import numpy.testing as npt
from caffe2.python import core, dataset, workspace
from caffe2.python.dataset import Const
from caffe2.python.schema import (
FeedRecord,
FetchRecord,
Field,
List,
Map,
... | 23,841 | 33.06 | 91 | py |
pytorch | pytorch-main/caffe2/python/operator_test/scale_op_test.py |
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
class TestScaleOps(serial.SerializedTestCase):
@serial.given(dim=st.sampled_from([[1, 386, 1], [... | 2,177 | 31.507463 | 68 | py |
pytorch | pytorch-main/caffe2/python/operator_test/mkl_conv_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given, settings
import numpy as np
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.mkl_test_util as mu
@unittest.skipIf(not workspace.C.has_mkldnn,
"Skipping a... | 1,547 | 28.769231 | 76 | py |
pytorch | pytorch-main/caffe2/python/operator_test/math_ops_test.py |
from caffe2.python import core
from hypothesis import given, settings
from hypothesis import strategies as st
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import numpy as np
import unittest
class TestMathOps(serial.SerializedTestCase):
... | 1,603 | 27.642857 | 75 | py |
pytorch | pytorch-main/caffe2/python/operator_test/rebatching_queue_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
import numpy.testing as npt
from hypothesis import given, settings
import hypothesis.strategies as st
import functools
def primefac(n):
ret = []
divisor = 2
while divisor * divisor <= n:
... | 9,045 | 30.301038 | 84 | py |
pytorch | pytorch-main/caffe2/python/operator_test/copy_ops_test.py |
import numpy as np
import unittest
from caffe2.proto import caffe2_pb2
from caffe2.python import workspace, core, model_helper, brew, test_util
class CopyOpsTest(test_util.TestCase):
def tearDown(self):
# Reset workspace after each test
# Otherwise, the multi-GPU test will use previously cr... | 7,374 | 38.021164 | 82 | py |
pytorch | pytorch-main/caffe2/python/operator_test/collect_and_distribute_fpn_rpn_proposals_op_test.py |
import numpy as np
import unittest
from hypothesis import given, settings
import hypothesis.strategies as st
from caffe2.python import core, utils
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
#
# Should match original Detectron code at
# htt... | 11,269 | 34.329154 | 111 | py |
pytorch | pytorch-main/caffe2/python/operator_test/weighted_multi_sample_test.py |
import numpy as np
from hypothesis import given
import hypothesis.strategies as st
from caffe2.python import core
from caffe2.python import workspace
import caffe2.python.hypothesis_test_util as hu
class TestWeightedMultiSample(hu.HypothesisTestCase):
@given(
num_samples=st.integers(min_value=0, ma... | 1,997 | 27.542857 | 82 | py |
pytorch | pytorch-main/caffe2/python/operator_test/im2col_col2im_test.py |
from caffe2.python import core
from hypothesis import assume, given, settings
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
class TestReduceFrontSum(hu.HypothesisTestCase):
@given(batch_size=st.integers(1, 3),
stride=st.integers(1, 3),
... | 4,311 | 30.021583 | 79 | py |
pytorch | pytorch-main/caffe2/python/test/gpu_context_test.py |
import unittest
import torch
from caffe2.python import core, workspace
# This is a standalone test that doesn't use test_util as we're testing
# initialization and thus we should be the ones calling GlobalInit
@unittest.skipIf(not workspace.has_cuda_support,
"THC pool testing is obscure and does... | 1,121 | 34.0625 | 75 | py |
pytorch | pytorch-main/caffe2/python/test/executor_test.py |
from caffe2.python import core, workspace
from caffe2.python.test.executor_test_util import (
build_conv_model,
build_resnet50_dataparallel_model,
run_resnet50_epoch,
ExecutorTestBase,
executor_test_settings,
executor_test_model_names)
from caffe2.python.test_util import TestCase
from hypo... | 3,039 | 28.230769 | 78 | py |
pytorch | pytorch-main/caffe2/python/test/fakefp16_transform_test.py |
import unittest
from caffe2.python.fakefp16_transform_lib import fakeFp16FuseOps
from caffe2.python import core
class Transformer(unittest.TestCase):
def test_fuse(self):
net_swish = core.Net("test_swish")
net_swish_init = core.Net("test_swish_init")
deq = core.CreateOperator("Int8Dequ... | 723 | 27.96 | 71 | py |
pytorch | pytorch-main/caffe2/python/test/inference_lstm_op_test.py | #!/usr/bin/env python3
import hypothesis.strategies as st
import numpy as np
import torch
from caffe2.python import core
from caffe2.python.test_util import TestCase
from hypothesis import given, settings
from torch import nn
class TestC2LSTM(TestCase):
@given(
bsz=st.integers(1, 5),
seq_lens=st.... | 2,190 | 29.013699 | 88 | py |
pytorch | pytorch-main/caffe2/python/test/executor_test_util.py |
from caffe2.python import (
brew, cnn, core, workspace, data_parallel_model,
timeout_guard, model_helper, optimizer)
from caffe2.python.test_util import TestCase
import caffe2.python.models.resnet as resnet
from caffe2.python.modeling.initializers import Initializer
from caffe2.python import convnet_benchm... | 8,058 | 29.070896 | 84 | py |
pytorch | pytorch-main/caffe2/python/test/do_op_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
import unittest
class DoOpTest(TestCase):
def test_operator(self):
def make_net():
subnet = core.Net('subnet')
subnet.Add(["X", "Y"], "Z")
net = core.Net("net"... | 2,055 | 25.358974 | 71 | py |
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