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/transformations_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... | 12,011 | 34.643917 | 110 | py |
pytorch | pytorch-main/caffe2/python/core_gradients_test.py |
from hypothesis import given, settings
import hypothesis.strategies as st
import unittest
from caffe2.proto import caffe2_pb2
from caffe2.python import core, test_util, workspace
from caffe2.python.core import CreateOperator, GradientRegistry, IR
import numpy as np
# First, we will set up a few gradient regist... | 38,019 | 36.60633 | 81 | py |
pytorch | pytorch-main/caffe2/python/lengths_reducer_rowwise_8bit_ops_test.py |
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import numpy as np
def FakeQuantization8BitsRowwise(data):
min_el = np.min(data, axis=1)
max_el = np.max(data, axis=1)
scale = (max_el - min_el) / 255.
bias = min_el
inv_scale = 1. / scale
data = da... | 5,710 | 36.572368 | 78 | py |
pytorch | pytorch-main/caffe2/python/checkpoint.py | ## @package checkpoint
# Module caffe2.python.checkpoint
import os
import logging
from caffe2.python import core, context
from caffe2.python.net_builder import ops
from caffe2.python.task import (
final_output,
Node,
Task,
TaskGroup,
TaskOutput,
WorkspaceType,
)
logger = logging.getLogger(... | 32,047 | 37.426859 | 87 | py |
pytorch | pytorch-main/caffe2/python/sparse_to_dense_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
class TestSparseToDense(TestCase):
def test_sparse_to_dense(self):
op = core.CreateOperator(
'SparseToDense',
['indices', 'values'],
['output'])
worksp... | 3,556 | 31.045045 | 75 | py |
pytorch | pytorch-main/caffe2/python/context.py | ## @package context
# Module caffe2.python.context
import inspect
import threading
import functools
class _ContextInfo:
def __init__(self, cls, allow_default):
self.cls = cls
self.allow_default = allow_default
self._local_stack = threading.local()
@property
def _stack(self):
... | 2,817 | 25.336449 | 98 | py |
pytorch | pytorch-main/caffe2/python/task_test.py | import unittest
from caffe2.python import task
class TestTask(unittest.TestCase):
def testRepr(self):
cases = [
(task.Cluster(), "Cluster(nodes=[], node_kwargs={})"),
(task.Node(), "Node(name=local, kwargs={})"),
(
task.TaskGroup(),
"Task... | 870 | 33.84 | 76 | py |
pytorch | pytorch-main/caffe2/python/core.py | ## @package core
# Module caffe2.python.core
from collections import namedtuple, OrderedDict, defaultdict
from past.builtins import basestring
from itertools import chain
from caffe2.proto import caffe2_pb2
from caffe2.python import scope, utils, workspace
from caffe2.python.lazy import TriggerLazyImport
from caf... | 118,950 | 37.733637 | 92 | py |
pytorch | pytorch-main/caffe2/python/convnet_benchmarks.py | ## @package convnet_benchmarks
# Module caffe2.python.convnet_benchmarks
"""
Benchmark for common convnets.
Speed on Titan X, with 10 warmup steps and 10 main steps and with different
versions of cudnn, are as follows (time reported below is per-batch time,
forward / forward+backward):
CuDNN V3 ... | 20,533 | 27.206044 | 81 | py |
pytorch | pytorch-main/caffe2/python/parallel_workers.py | # @package parallel_workers
# Module caffe2.python.parallel_workers
'''
This module provides a python-land multithreaded mechanism for executing work.
Basic usage is as follows:
coordinator = parallel_workers.init_workers(
my_worker_fun,
worker_name="train"
)
...
coordinator.start()
Firs... | 7,650 | 24.935593 | 80 | py |
pytorch | pytorch-main/caffe2/python/dataio.py | ## @package dataio
# Module caffe2.python.dataio
"""
Defines the base interface for reading and writing operations.
Readers/Writers are objects that produce operations that read/write sequences
of data. Each operation reads or writes a list of BlobReferences.
Readers and Writers must be implemented such that read and... | 23,391 | 35.779874 | 113 | py |
pytorch | pytorch-main/caffe2/python/net_builder.py | ## @package net_builder
# Module caffe2.python.net_builder
from caffe2.python import core, context
from caffe2.python.task import Task, TaskGroup
from caffe2.python.control_ops_util import add_if_op, add_while_op
class NetBuilder(context.Managed):
"""
Scope-driven mechanism for building nets, loops and c... | 27,655 | 36.172043 | 82 | py |
pytorch | pytorch-main/caffe2/python/clean_workspace_test.py | import unittest
from caffe2.python import workspace
# This test is extracted out from workspace_test.py because it relies on the pristine
# state of the initial workspace. When tests are run in different orders, this test may
# become flaky because of global state modifications impacting what the root folder is
# af... | 680 | 41.5625 | 87 | py |
pytorch | pytorch-main/caffe2/python/caffe_translator.py | ## @package caffe_translator
# Module caffe2.python.caffe_translator
import argparse
import copy
import logging
import re
import numpy as np # noqa
from caffe2.proto import caffe2_pb2, caffe2_legacy_pb2
from caffe.proto import caffe_pb2
from caffe2.python import core, utils, workspace
from google.protobuf import tex... | 35,231 | 36.560768 | 91 | py |
pytorch | pytorch-main/caffe2/python/ideep_test_util.py | ## @package ideep_test_util
# Module caffe2.python.ideep_test_util
"""
The IDEEP test utils is a small addition on top of the hypothesis test utils
under caffe2/python, which allows one to more easily test IDEEP related
operators.
"""
import hypothesis.strategies as st
from caffe2.proto import caffe2_pb2
from ca... | 998 | 23.975 | 92 | py |
pytorch | pytorch-main/caffe2/python/layer_parameter_sharing_test.py |
from caffe2.python import core, scope
from caffe2.python.modeling.parameter_sharing import (
ParameterSharing,
)
from caffe2.python.optimizer import AdagradOptimizer, AdamOptimizer
from caffe2.python.layer_test_util import LayersTestCase
class ParameterSharingTest(LayersTestCase):
def test_layer_paramet... | 9,132 | 38.197425 | 86 | py |
pytorch | pytorch-main/caffe2/python/allcompare_test.py | #!/usr/bin/env python3
from hypothesis import given, settings
import hypothesis.strategies as st
from multiprocessing import Process
import numpy as np
import tempfile
import shutil
import caffe2.python.hypothesis_test_util as hu
op_engine = 'GLOO'
class TemporaryDirectory:
def __enter__(self):
s... | 2,255 | 24.636364 | 79 | py |
pytorch | pytorch-main/caffe2/python/context_test.py |
from caffe2.python import context, test_util
from threading import Thread
class MyContext(context.Managed):
pass
class DefaultMyContext(context.DefaultManaged):
pass
class ChildMyContext(MyContext):
pass
class TestContext(test_util.TestCase):
def use_my_context(self):
try:
... | 1,792 | 25.367647 | 75 | py |
pytorch | pytorch-main/caffe2/python/sparse_to_dense_mask_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
class TestSparseToDenseMask(TestCase):
def test_sparse_to_dense_mask_float(self):
op = core.CreateOperator(
'SparseToDenseMask',
['indices', 'values', 'default', 'lengths... | 6,565 | 40.556962 | 77 | py |
pytorch | pytorch-main/caffe2/python/db_test.py |
from caffe2.python import workspace
import os
import tempfile
import unittest
class TestDB(unittest.TestCase):
def setUp(self):
handle, self.file_name = tempfile.mkstemp()
os.close(handle)
self.data = [
(
"key{}".format(i).encode("ascii"),
... | 1,110 | 22.638298 | 61 | py |
pytorch | pytorch-main/caffe2/python/nomnigraph_test.py |
from caffe2.python import core, test_util
from caffe2.proto import caffe2_pb2
import caffe2.python.nomnigraph as ng
from hypothesis import given
import hypothesis.strategies as st
import random
class TestBindings(test_util.TestCase):
def test_simple(self):
nn = ng.NNModule()
dfg = nn.dataFlo... | 15,427 | 33.747748 | 81 | py |
pytorch | pytorch-main/caffe2/python/regularizer_context.py | # @package regularizer_context
# Module caffe2.python.regularizer_context
from caffe2.python import context
from caffe2.python.modifier_context import (
ModifierContext, UseModifierBase)
class RegularizerContext(ModifierContext, context.DefaultManaged):
"""
provide context to allow param_info to have... | 1,013 | 25.684211 | 70 | py |
pytorch | pytorch-main/caffe2/python/hsm_util.py | ## @package hsm_util
# Module caffe2.python.hsm_util
from caffe2.proto import hsm_pb2
'''
Hierarchical softmax utility methods that can be used to:
1) create TreeProto structure given list of word_ids or NodeProtos
2) create HierarchyProto structure using the user-inputted TreeProto
'''
def create_n... | 2,259 | 30.830986 | 78 | py |
pytorch | pytorch-main/caffe2/python/test_util.py | ## @package test_util
# Module caffe2.python.test_util
import numpy as np
from caffe2.python import core, workspace
import os
import pathlib
import shutil
import tempfile
import unittest
from typing import Any, Callable, Tuple, Type
from types import TracebackType
def rand_array(*dims):
# np.random.rand() re... | 3,524 | 29.387931 | 85 | py |
pytorch | pytorch-main/caffe2/python/crf_viterbi_test.py |
from caffe2.python import workspace, crf
from caffe2.python.cnn import CNNModelHelper
from caffe2.python.crf_predict import crf_update_predictions
from caffe2.python.test_util import TestCase
import hypothesis.strategies as st
from hypothesis import given, settings
import numpy as np
class TestCrfDecode(TestCase... | 1,663 | 34.404255 | 77 | py |
pytorch | pytorch-main/caffe2/python/normalizer.py | # @package optimizer
# Module caffe2.python.normalizer
class Normalizer:
def __init__(self):
pass
"""
Adds normalization to train_net for given parameter. Its factor ahead of
regularization is given when initialization.
The param should be a BlobReference.
"""
def __call__(self, ... | 1,361 | 29.266667 | 124 | py |
pytorch | pytorch-main/caffe2/python/model_helper_test.py | """unittest for ModelHelper class"""
import unittest
from caffe2.python import brew, model_helper
class ModelHelperTest(unittest.TestCase):
def test_get_complete_net_type(self):
model = model_helper.ModelHelper("test_orig")
brew.conv(
model,
"input",
"conv",... | 2,336 | 32.385714 | 87 | py |
pytorch | pytorch-main/caffe2/python/crf_predict.py |
import numpy as np
from caffe2.python.crf import CRFWithLoss
def crf_update_predictions(model, crf_with_loss, classes):
return apply_crf(
model.param_init_net,
model.net,
crf_with_loss.transitions,
classes,
crf_with_loss.num_classes,
)
def apply_crf(init_net, net, t... | 1,159 | 33.117647 | 77 | py |
pytorch | pytorch-main/caffe2/python/caffe_translator_test.py | # This a large test that goes through the translation of the bvlc caffenet
# model, runs an example through the whole model, and verifies numerically
# that all the results look right. In default, it is disabled unless you
# explicitly want to run it.
from google.protobuf import text_format
import numpy as np
import o... | 3,553 | 38.054945 | 81 | py |
pytorch | pytorch-main/caffe2/python/task.py | ## @package task
# Module caffe2.python.task
from caffe2.python import core, context
from caffe2.python.schema import Field, from_blob_list
from collections import defaultdict
from copy import copy
def _merge_node_kwargs(a, b):
# TODO(azzolini): consistency checks
if a is None:
return b
if b is N... | 24,181 | 33.894661 | 81 | py |
pytorch | pytorch-main/caffe2/python/checkpoint_test.py |
from caffe2.python.schema import Struct, ConstRecord
from caffe2.python import core, workspace, model_helper
from caffe2.python.session import LocalSession
from caffe2.python.dataset import Dataset
from caffe2.python.pipeline import pipe
from caffe2.python.checkpoint import (
CheckpointManager, MultiNodeCheckp... | 13,393 | 38.510324 | 88 | py |
pytorch | pytorch-main/caffe2/python/device_checker.py | ## @package device_checker
# Module caffe2.python.device_checker
import numpy as np
import copy
from caffe2.python import workspace
from caffe2.python.core import InferOpBlobDevicesAsDict
class DeviceChecker:
"""A device checker in Python to check consistency across multiple devices.
This is not the most eff... | 5,111 | 41.6 | 81 | py |
pytorch | pytorch-main/caffe2/python/cnn.py | ## @package cnn
# Module caffe2.python.cnn
from caffe2.python import brew, workspace
from caffe2.python.model_helper import ModelHelper
from caffe2.proto import caffe2_pb2
import logging
class CNNModelHelper(ModelHelper):
"""A helper model so we can write CNN models more easily, without having to
manuall... | 7,606 | 30.564315 | 80 | py |
pytorch | pytorch-main/caffe2/python/parallelize_bmuf_distributed_test.py |
from multiprocessing import Process, Manager
import numpy as np
import unittest
import tempfile
import shutil
import logging
from hypothesis import given, settings
import hypothesis.strategies as st
from caffe2.python import workspace
log = logging.getLogger("parallelize_bmuf_distributed_test")
log.setLevel(log... | 9,908 | 32.589831 | 86 | py |
pytorch | pytorch-main/caffe2/python/observer_test.py |
import numpy as np
import unittest
from hypothesis import given, settings
import hypothesis.strategies as st
from caffe2.python import brew, core, model_helper, rnn_cell
import caffe2.python.workspace as ws
class TestObservers(unittest.TestCase):
def setUp(self):
core.GlobalInit(["python", "caffe2"]... | 5,316 | 33.303226 | 88 | py |
pytorch | pytorch-main/caffe2/python/brew.py | ## @package model_helper_api
# Module caffe2.python.model_helper_api
import sys
import copy
import inspect
from past.builtins import basestring
from caffe2.python.model_helper import ModelHelper
# flake8: noqa
from caffe2.python.helpers.algebra import *
from caffe2.python.helpers.arg_scope import *
from caffe2.py... | 4,762 | 33.021429 | 89 | py |
pytorch | pytorch-main/caffe2/python/scope.py | ## @package scope
# Module caffe2.python.scope
import contextlib
import threading
from past.builtins import basestring
from caffe2.proto import caffe2_pb2
# The name scope and device scope when creating a new operator.
_NAMESCOPE_SEPARATOR = '/'
_threadlocal_scope = threading.local()
def CurrentNameScope():
... | 3,623 | 28.463415 | 83 | py |
pytorch | pytorch-main/caffe2/python/operator_fp_exceptions_test.py |
from caffe2.python import core, workspace
from caffe2.python.test_util import TestCase
import numpy as np
import unittest
def setThrowIfFpExceptions(enabled):
core.GlobalInit(["caffe2", "--caffe2_operator_throw_if_fp_exceptions=%d" % (1 if enabled else 0)])
class OperatorFPExceptionsTest(TestCase):
def... | 1,247 | 29.439024 | 102 | py |
pytorch | pytorch-main/caffe2/python/control_ops_util.py | ## @package control_ops_util
# Module caffe2.python.control_ops_util
from caffe2.python import core
def get_external_blob_names(net, lexical_scope):
"""
Returns a set of blobs a given net depends on and a set of
output blobs that are written by the net
Inputs:
net - net to return input/ou... | 10,863 | 40.151515 | 88 | py |
pytorch | pytorch-main/caffe2/python/control_ops_grad_test.py |
import unittest
from caffe2.python import core, test_util, workspace
from caffe2.python.control_ops_grad import disambiguate_grad_if_op_output
from caffe2.python.model_helper import ModelHelper
import numpy as np
class TestControl(test_util.TestCase):
def test_disambiguate_grad_if_op_output(self):
wo... | 1,752 | 34.06 | 79 | py |
pytorch | pytorch-main/caffe2/python/record_queue.py | ## @package record_queue
# Module caffe2.python.record_queue
"""
Implementation of a queue wrapper.
"""
from caffe2.python import core
from caffe2.python.dataio import Reader, Writer
from caffe2.python.schema import (
Struct, Field, from_column_list)
class _QueueReader(Reader):
def __init__(self, blobs_q... | 4,427 | 36.210084 | 80 | py |
pytorch | pytorch-main/caffe2/python/lengths_reducer_fused_8bit_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
def compare_rowwise(emb_orig, emb_reconstructed, fp16):
# there is an absolute error introduced per row through int8 quantization
# and... | 7,575 | 36.320197 | 87 | py |
pytorch | pytorch-main/caffe2/python/tt_core.py | ## @package tt_core
# Module caffe2.python.tt_core
import numpy as np
"""
The following methods are various utility methods for using the Tensor-Train
decomposition, or TT-decomposition introduced by I. V. Oseledets (2011) in his
paper (http://epubs.siam.org/doi/abs/10.1137/090752286).
Broadly speaking, these met... | 9,349 | 37.636364 | 80 | py |
pytorch | pytorch-main/caffe2/python/rnn_cell.py | ## @package rnn_cell
# Module caffe2.python.rnn_cell
import functools
import inspect
import logging
import numpy as np
import random
from caffe2.proto import caffe2_pb2
from caffe2.python.attention import (
apply_dot_attention,
apply_recurrent_attention,
apply_regular_attention,
apply_soft_coverag... | 67,985 | 33.353714 | 83 | py |
pytorch | pytorch-main/caffe2/python/workspace.py | ## @package workspace
# Module caffe2.python.workspace
import collections
import contextlib
from google.protobuf.message import Message
from multiprocessing import Process
import os
from collections import defaultdict
import logging
import numpy as np
from past.builtins import basestring
import shutil
import socket... | 25,352 | 31.33801 | 90 | py |
pytorch | pytorch-main/caffe2/python/functional.py |
from caffe2.python import core, workspace
from caffe2.proto import caffe2_pb2
from caffe2.python.onnx.workspace import Workspace
from collections import namedtuple
OpSchema = workspace.C.OpSchema
def namedtupledict(typename, field_names, *args, **kwargs):
field_names_map = {n: i for i, n in enumerate(field_... | 4,369 | 37.333333 | 88 | py |
pytorch | pytorch-main/caffe2/python/numa_benchmark.py |
from caffe2.python import core, workspace
from caffe2.proto import caffe2_pb2
import time
SHAPE_LEN = 4096
NUM_ITER = 1000
GB = 1024 * 1024 * 1024
NUM_REPLICAS = 48
def build_net(net_name, cross_socket):
init_net = core.Net(net_name + "_init")
init_net.Proto().type = "async_scheduling"
numa_device_op... | 2,230 | 30.871429 | 81 | py |
pytorch | pytorch-main/caffe2/python/hypothesis_test_util.py | ## @package hypothesis_test_util
# Module caffe2.python.hypothesis_test_util
"""
The Hypothesis library uses *property-based testing* to check
invariants about the code under test under a variety of random inputs.
The key idea here is to express properties of the code under test
(e.g. that it passes a gradient check,... | 26,853 | 34.710106 | 99 | py |
pytorch | pytorch-main/caffe2/python/utils.py | # @package utils
# Module caffe2.python.utils
from caffe2.proto import caffe2_pb2
from google.protobuf.message import DecodeError, Message
from google.protobuf import text_format
import sys
import collections
import copy
import functools
import numpy as np
OPTIMIZER_ITERATION_NAME = "optimizer_iteration"
OPTIMIZ... | 14,061 | 31.702326 | 110 | py |
pytorch | pytorch-main/caffe2/python/memonger_test.py | import numpy as np
from caffe2.python import workspace, memonger, core, model_helper, brew
from caffe2.proto import caffe2_pb2
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
from hypothesis import given, settings
import unittest
def has_blob(proto, needle):
for op in proto.op:... | 36,858 | 42.775534 | 87 | py |
pytorch | pytorch-main/caffe2/python/transformations.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... | 1,824 | 29.932203 | 87 | py |
pytorch | pytorch-main/caffe2/python/dataset.py | ## @package dataset
# Module caffe2.python.dataset
"""
Implementation of an in-memory dataset with structured schema.
Use this to store and iterate through datasets with complex schema that
fit in memory.
Iterating through entries of this dataset is very fast since the dataset
is stored as a set of native Caffe2 tens... | 12,878 | 36.330435 | 79 | py |
pytorch | pytorch-main/caffe2/python/nomnigraph_transformations_test.py |
from caffe2.python import core, workspace
from caffe2.python import test_util as tu
import caffe2.python.nomnigraph as ng
from caffe2.python.nomnigraph_transformations import transpose_network
import numpy as np
from hypothesis import given
import hypothesis.strategies as st
class TestNomnigraphTransformations(... | 5,767 | 38.77931 | 88 | py |
pytorch | pytorch-main/caffe2/python/layer_model_instantiator.py | ## @package layer_model_instantiator
# Module caffe2.python.layer_model_instantiator
from caffe2.python import core, schema
from caffe2.python.layers.layers import InstantiationContext
from caffe2.python.layers.tags import Tags
def _filter_layers(layers, include_tags):
if include_tags is None:
return... | 3,935 | 33.526316 | 81 | py |
pytorch | pytorch-main/caffe2/python/normalizer_test.py |
from caffe2.python.normalizer_context import UseNormalizer, NormalizerContext
from caffe2.python.normalizer import BatchNormalizer
from caffe2.python.layer_test_util import LayersTestCase
class TestNormalizerContext(LayersTestCase):
def test_normalizer_context(self):
bn = BatchNormalizer(momentum=0.1)... | 486 | 29.4375 | 77 | py |
pytorch | pytorch-main/caffe2/python/convert_test.py |
from caffe2.python import workspace
import unittest
class TestOperator(unittest.TestCase):
def setUp(self):
workspace.ResetWorkspace()
if __name__ == '__main__':
unittest.main()
| 201 | 12.466667 | 38 | py |
pytorch | pytorch-main/caffe2/python/muji_test.py | import numpy as np
import unittest
from caffe2.python import core, workspace, muji, test_util
@unittest.skipIf(not workspace.has_gpu_support, "no gpu")
class TestMuji(test_util.TestCase):
def RunningAllreduceWithGPUs(self, gpu_ids, allreduce_function):
"""A base function to test different scenarios."""
... | 3,058 | 35.855422 | 91 | py |
pytorch | pytorch-main/caffe2/python/numa_test.py |
from caffe2.python import core, workspace
from caffe2.proto import caffe2_pb2
from caffe2.python.test_util import TestCase
import unittest
core.GlobalInit(["caffe2", "--caffe2_cpu_numa_enabled=1"])
def build_test_net(net_name):
net = core.Net(net_name)
net.Proto().type = "async_scheduling"
numa_devic... | 1,663 | 29.814815 | 74 | py |
pytorch | pytorch-main/caffe2/python/lazy_dyndep.py | ## @package lazy_dyndep
# Module caffe2.python.lazy_dyndep
import os
from caffe2.python import dyndep, lazy
def RegisterOpsLibrary(name):
"""Registers a dynamic library that contains custom operators into Caffe2.
Since Caffe2 uses static variable registration, you can optionally load a
separate .so ... | 2,562 | 29.152941 | 83 | py |
pytorch | pytorch-main/caffe2/python/control.py | ## @package control
# Module caffe2.python.control
"""
Implement functions for controlling execution of nets and steps, including
Do
DoParallel
For-loop
While-loop
Do-While-loop
Switch
If
"""
from caffe2.python import core
# Used to generate names of the steps created by the control functions.
# I... | 19,271 | 32.516522 | 80 | py |
pytorch | pytorch-main/caffe2/python/hip_test_util.py | ## @package hip_test_util
# Module caffe2.python.hip_test_util
"""
The HIP test utils is a small addition on top of the hypothesis test utils
under caffe2/python, which allows one to more easily test HIP/ROCm related
operators.
"""
from caffe2.proto import caffe2_pb2
def run_in_hip(gc, dc):
return (gc.device... | 405 | 20.368421 | 74 | py |
pytorch | pytorch-main/caffe2/python/embedding_generation_benchmark.py | ## @package embedding_generation_benchmark
# Module caffe2.python.embedding_generation_benchmark
from caffe2.proto import caffe2_pb2
from caffe2.python import workspace, core, utils, model_helper
import argparse
import numpy as np
import time
import logging
logging.basicConfig()
log = logging.getLogger("embeddi... | 5,256 | 25.685279 | 75 | py |
pytorch | pytorch-main/caffe2/python/experiment_util.py | ## @package experiment_util
# Module caffe2.python.experiment_util
import datetime
import time
import logging
import socket
import abc
from collections import OrderedDict
'''
Utilities for logging experiment run stats, such as accuracy
and loss over time for different runs. Runtime arguments are stored
in the lo... | 3,562 | 30.254386 | 74 | py |
pytorch | pytorch-main/caffe2/python/mkl_test_util.py | ## @package mkl_test_util
# Module caffe2.python.mkl_test_util
"""
The MKL test utils is a small addition on top of the hypothesis test utils
under caffe2/python, which allows one to more easily test MKL related
operators.
"""
import hypothesis.strategies as st
from caffe2.proto import caffe2_pb2
from caffe2.pyt... | 1,142 | 24.4 | 86 | py |
pytorch | pytorch-main/caffe2/python/fakefp16_transform_lib.py | #!/usr/bin/env python3
import caffe2.python._import_c_extension as C
from caffe2.proto.caffe2_pb2 import NetDef
def fakeFp16FuseOps(net : NetDef) -> NetDef:
net_str = net.SerializeToString()
out_str = C.fakeFp16FuseOps(net_str)
out_net = NetDef()
out_net.ParseFromString(out_str)
return out_ne... | 322 | 18 | 45 | py |
pytorch | pytorch-main/caffe2/python/predictor_constants.py | ## @package predictor_constants
# Module caffe2.python.predictor_constants
import caffe2.proto.predictor_consts_pb2 as predictor_consts
predictor_constants = predictor_consts.PredictorConsts()
| 198 | 18.9 | 60 | py |
pytorch | pytorch-main/caffe2/python/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
class CustomError(Exception):
pass
def SubFunctionThatThrowsCustomError()... | 9,169 | 36.276423 | 97 | py |
pytorch | pytorch-main/caffe2/python/regularizer.py | # @package optimizer
# Module caffe2.python.regularizer
from caffe2.python import core, utils
import numpy as np
class RegularizationBy:
AFTER_OPTIMIZER = "after_optimizer"
ON_LOSS = "on_loss"
class Regularizer:
def __init__(self):
self.kEpsilon = 1e-9
"""
Adds regularization to train... | 20,837 | 36.887273 | 133 | py |
pytorch | pytorch-main/caffe2/python/recurrent.py | ## @package recurrent
# Module caffe2.python.recurrent
from caffe2.python import core, workspace
def recurrent_net(
net, cell_net, inputs, initial_cell_inputs,
links, timestep=None, scope=None, outputs_with_grads=(0,),
recompute_blobs_on_backward=None, forward_only=False,
):
'''
ne... | 13,243 | 38.771772 | 80 | py |
pytorch | pytorch-main/caffe2/python/tt_core_test.py |
import numpy as np
import unittest
from caffe2.python import core, workspace, tt_core
import caffe2.python.hypothesis_test_util as hu
class TestTTSVD(hu.HypothesisTestCase):
def test_full_tt_svd(self):
size = 256
np.random.seed(1234)
X = np.expand_dims(
np.random.rand(siz... | 2,516 | 29.325301 | 79 | py |
pytorch | pytorch-main/caffe2/python/extension_loader.py | ## @package extension_loader
# Module caffe2.python.extension_loader
import contextlib
import ctypes
import sys
_set_global_flags = (
hasattr(sys, 'getdlopenflags') and hasattr(sys, 'setdlopenflags'))
@contextlib.contextmanager
def DlopenGuard(extra_flags=ctypes.RTLD_GLOBAL):
if _set_global_flags:
... | 744 | 23.833333 | 80 | py |
pytorch | pytorch-main/caffe2/python/data_parallel_model.py | ## @package data_parallel_model
# Module caffe2.python.data_parallel_model
from collections import OrderedDict
import logging
import copy
from multiprocessing import cpu_count
from caffe2.python import \
model_helper, dyndep, scope, workspace, core, memonger, utils
from caffe2.proto import caffe2_pb2
import ... | 82,978 | 36.344284 | 107 | py |
pytorch | pytorch-main/caffe2/python/model_helper.py | ## @package model_helper
# Module caffe2.python.model_helper
from caffe2.python import core, scope, workspace
from caffe2.python.helpers.db_input import db_input
from caffe2.python.modeling import parameter_info
from caffe2.python.modeling.parameter_sharing import (
parameter_sharing_context,
)
from caffe2.pyt... | 23,457 | 35.256569 | 86 | py |
pytorch | pytorch-main/caffe2/python/lazy_dyndep_test.py | #!/usr/bin/env python3
from hypothesis import given, settings
import hypothesis.strategies as st
from multiprocessing import Process
import numpy as np
import tempfile
import shutil
import caffe2.python.hypothesis_test_util as hu
import unittest
op_engine = 'GLOO'
class TemporaryDirectory:
def __enter__(s... | 3,914 | 28.216418 | 96 | py |
pytorch | pytorch-main/caffe2/python/crf.py | ## @package crf
# Module caffe2.python.crf
import numpy as np
from caffe2.python import brew, core, model_helper, recurrent
"""
Due to a limitation in ReccurentNetworkOp, this layer only supports batch_size=1
In order to support batch_size > 1, we will have to implement the CRFUnit
and its gradient in C++ and handl... | 13,242 | 41.175159 | 86 | py |
pytorch | pytorch-main/caffe2/python/schema_test.py |
from caffe2.python import core, schema
import numpy as np
import unittest
import pickle
import random
class TestField(unittest.TestCase):
def testInitShouldSetEmptyParent(self):
f = schema.Field([])
self.assertTupleEqual(f._parent, (None, 0))
def testInitShouldSetFieldOffsets(self):
... | 15,725 | 32.317797 | 81 | py |
pytorch | pytorch-main/caffe2/python/nomnigraph_transformations.py |
from collections import defaultdict
import caffe2.python.nomnigraph as ng
from caffe2.python import core, utils
def transpose_network(nn):
"""
Convert all Convolutions operators which are in the NCHW order
to NHWC order and also transform their inputs and outputs so that the
rest of the graph is no... | 3,787 | 41.561798 | 79 | py |
pytorch | pytorch-main/caffe2/python/timeout_guard.py | ## @package timeout_guard
# Module caffe2.python.timeout_guard
import contextlib
import threading
import os
import time
import signal
import logging
'''
Sometimes CUDA devices can get stuck, 'deadlock'. In this case it is often
better just the kill the process automatically. Use this guard to set a
maximum times... | 4,013 | 34.210526 | 96 | py |
pytorch | pytorch-main/caffe2/python/gradient_check_test.py | # TODO(jiayq): as more and more tests are moving to hypothesis test, we
# can gradually remove this test script. DO NOT ADD MORE TESTS TO THIS
# FILE.
import numpy as np
from caffe2.python import (
brew,
core,
device_checker,
gradient_checker,
model_helper,
test_util,
workspace,
)
from ... | 20,729 | 36.150538 | 84 | py |
pytorch | pytorch-main/caffe2/python/session.py | ## @package session
# Module caffe2.python.session
from caffe2.python import core, workspace
from caffe2.python.task import Cluster, Task, TaskGroup, WorkspaceType
class CompiledRunnable:
""" Wrapper for compiled runnable returned from session.compile() """
def __init__(self, obj, session_class):
... | 7,626 | 34.640187 | 88 | py |
pytorch | pytorch-main/caffe2/python/data_parallel_model_test.py |
from multiprocessing import Process, Queue
import numpy as np
import os
import shutil
import tempfile
import unittest
import time
from mock import Mock
from hypothesis import assume, given, settings
import hypothesis.strategies as st
from caffe2.proto import caffe2_pb2
from caffe2.python import brew, core, cnn, da... | 56,108 | 38.292017 | 174 | py |
pytorch | pytorch-main/caffe2/python/net_drawer.py | ## @package net_drawer
# Module caffe2.python.net_drawer
import argparse
import json
import logging
from collections import defaultdict
from caffe2.python import utils
logger = logging.getLogger(__name__)
logger.setLevel(logging.INFO)
try:
import pydot
except ImportError:
logger.info(
'Cannot impo... | 14,226 | 33.531553 | 80 | py |
pytorch | pytorch-main/caffe2/python/model_device_test.py | import numpy as np
import unittest
from caffe2.proto import caffe2_pb2
from caffe2.python import (
workspace,
device_checker,
test_util,
model_helper,
brew,
)
class TestMiniAlexNet(test_util.TestCase):
def _MiniAlexNetNoDropout(self, order):
# First, AlexNet using the cnn wrapper.
... | 4,777 | 30.228758 | 80 | py |
pytorch | pytorch-main/caffe2/python/convnet_benchmarks_test.py | import unittest
from caffe2.python import convnet_benchmarks as cb
from caffe2.python import test_util, workspace
# TODO: investigate why this randomly core dump in ROCM CI
@unittest.skipIf(not workspace.has_cuda_support, "no cuda gpu")
class TestConvnetBenchmarks(test_util.TestCase):
def testConvnetBenchmarks(se... | 839 | 34 | 76 | py |
pytorch | pytorch-main/caffe2/python/optimizer_test.py |
from caffe2.proto import caffe2_pb2
import caffe2.python.optimizer as optimizer
from caffe2.python.optimizer import (
build_sgd, build_multi_precision_sgd, build_ftrl, build_gftrl, build_wngrad,
build_adagrad, build_adadelta, build_adam, build_yellowfin, build_rms_prop,
build_storm, build_decay_adagrad, ... | 31,622 | 39.64653 | 120 | py |
pytorch | pytorch-main/caffe2/python/brew_test.py |
from caffe2.python import brew, core, scope, workspace
from caffe2.python.modeling.parameter_info import ParameterTags
from caffe2.python.model_helper import ModelHelper
from caffe2.python.cnn import CNNModelHelper
import unittest
import numpy as np
class BrewTest(unittest.TestCase):
def setUp(self):
... | 11,739 | 34.683891 | 83 | py |
pytorch | pytorch-main/caffe2/python/layers_test.py |
import hypothesis.strategies as st
import numpy as np
import numpy.testing as npt
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
from caffe2.python import (
layer_model_instantiator,
core,
schema,
workspace,
)
from caffe2.python.layers.layers import (
A... | 92,930 | 35.921335 | 122 | py |
pytorch | pytorch-main/caffe2/python/filler_test.py |
from caffe2.python import core, test_util, workspace
class TestFiller(test_util.TestCase):
def test_filler(self):
net = core.Net("test_filler")
net.Concat(["X0", "X1", "X2"], ["concat_out", "split_info"])
self.assertFalse(workspace.HasBlob("X0"))
input_dim = (30, 20)
wo... | 748 | 34.666667 | 114 | py |
pytorch | pytorch-main/caffe2/python/data_workers.py | ## @package data_workers
# Module caffe2.python.data_workers
'''
This module provides a python-land multithreaded data input mechanism
for Caffe2 nets.
Basic usage is as follows:
coordinator = data_workers.init_data_input_workers(
net,
["data", "label"],
my_fetch_fun,
batch_size=32,
... | 15,941 | 33.506494 | 96 | py |
pytorch | pytorch-main/caffe2/python/convert.py | ## @package workspace
# Module caffe2.python.workspace
| 55 | 17.666667 | 32 | py |
pytorch | pytorch-main/caffe2/python/__init__.py | import os
import sys
import warnings
try:
from caffe2.proto import caffe2_pb2
except ImportError:
warnings.warn('Caffe2 support is not enabled in this PyTorch build. '
'Please enable Caffe2 by building PyTorch from source with `BUILD_CAFFE2=1` flag.')
raise
# TODO: refactor & remove the... | 3,754 | 41.670455 | 108 | py |
pytorch | pytorch-main/caffe2/python/core_test.py |
from inspect import currentframe, getframeinfo
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace, schema, test_util
from caffe2.python.task import Node, Task
class TestScopes(test_util.TestCase):
def testBlobReferenceIsIndependentFromNameScope(... | 47,678 | 36.690909 | 93 | py |
pytorch | pytorch-main/caffe2/python/fused_8bit_rowwise_conversion_ops_test.py |
from caffe2.python import core, workspace
import caffe2.python.hypothesis_test_util as hu
import numpy as np
import struct
from hypothesis import given
# Eigen/Python round 0.5 away from 0, Numpy rounds to even
round_to_nearest = np.vectorize(round)
def bytes_to_floats(byte_matrix):
floats = np.empty([np.s... | 3,991 | 36.308411 | 93 | py |
pytorch | pytorch-main/caffe2/python/cached_reader.py | ## @package cached_reader
# Module caffe2.python.cached_reader
import os
from caffe2.python import core
from caffe2.python.db_file_reader import DBFileReader
from caffe2.python.pipeline import pipe
from caffe2.python.task import Cluster, TaskGroup
class CachedReader(DBFileReader):
default_name_suffix = 'ca... | 4,376 | 31.664179 | 82 | py |
pytorch | pytorch-main/caffe2/python/hypothesis_test.py | import numpy as np
import copy
import time
from functools import partial, reduce
from hypothesis import assume, given, settings, HealthCheck
import hypothesis.strategies as st
import unittest
import threading
from caffe2.python import core, workspace, tt_core, dyndep
import caffe2.python.hypothesis_test_util as hu
fro... | 105,855 | 36.792217 | 101 | py |
pytorch | pytorch-main/caffe2/python/parallel_workers_test.py |
import unittest
from caffe2.python import workspace, core
import caffe2.python.parallel_workers as parallel_workers
def create_queue():
queue = 'queue'
workspace.RunOperatorOnce(
core.CreateOperator(
"CreateBlobsQueue", [], [queue], num_blobs=1, capacity=1000
)
)
# T... | 3,501 | 28.183333 | 90 | py |
pytorch | pytorch-main/caffe2/python/utils_test.py |
from caffe2.python import core, utils, test_util
import numpy as np
class TestUtils(test_util.TestCase):
def testArgsToDict(self):
args = [utils.MakeArgument("int1", 3),
utils.MakeArgument("float1", 4.0),
utils.MakeArgument("string1", "foo"),
utils.Mak... | 1,399 | 33.146341 | 76 | py |
pytorch | pytorch-main/caffe2/python/optimizer_test_util.py | ## @package optimizer_test_util
# Module caffe2.python.optimizer_test_util
import unittest
import numpy as np
from caffe2.python import brew, core, workspace, cnn, optimizer
from caffe2.python.modeling.initializers import (
Initializer, PseudoFP16Initializer)
from caffe2.python.model_helper import ModelHelper... | 9,171 | 37.537815 | 80 | py |
pytorch | pytorch-main/caffe2/python/net_printer.py | ## @package net_printer
# Module caffe2.python.net_printer
from caffe2.proto.caffe2_pb2 import OperatorDef, NetDef
from caffe2.python.checkpoint import Job
from caffe2.python.core import Net, ExecutionStep, Plan
from caffe2.python.task import Task, TaskGroup, WorkspaceType, TaskOutput
from collections import defau... | 12,689 | 28.858824 | 80 | py |
pytorch | pytorch-main/caffe2/python/attention.py | ## @package attention
# Module caffe2.python.attention
from caffe2.python import brew
class AttentionType:
Regular, Recurrent, Dot, SoftCoverage = tuple(range(4))
def s(scope, name):
# We have to manually scope due to our internal/external blob
# relationships.
return "{}/{}".format(str(scope),... | 12,359 | 28.082353 | 78 | py |
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