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
value |
|---|---|---|---|---|---|---|
pytorch | pytorch-main/caffe2/python/lazy.py | ## @package workspace
# Module caffe2.python.lazy
_import_lazy_calls = []
def RegisterLazyImport(lazy):
global _import_lazy_calls
_import_lazy_calls += [lazy]
def TriggerLazyImport():
global _import_lazy_calls
for lazy in _import_lazy_calls:
lazy()
| 277 | 17.533333 | 35 | py |
pytorch | pytorch-main/caffe2/python/memonger.py | ## @package memonger
# Module caffe2.python.memonger
import networkx as nx
import collections
import time
import copy
from caffe2.python import workspace, core
from caffe2.proto import caffe2_pb2
import enum
import logging
import caffe2.python._import_c_extension as C
log = logging.getLogger("memonger")
log.setLe... | 34,537 | 33.469062 | 117 | py |
pytorch | pytorch-main/caffe2/python/regularizer_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, layer_model_instantiator, regularizer, schema, workspace
from caffe2.python.layer_test_util import LayersTestCase
from caffe2.python.optimizer import SgdOpt... | 10,266 | 38.640927 | 104 | py |
pytorch | pytorch-main/caffe2/python/nomnigraph.py |
import errno
import os
from subprocess import PIPE, Popen
import caffe2.python._import_c_extension as C
from caffe2.proto import caffe2_pb2
from caffe2.python import core
class NNModule:
def __init__(self, net=None, device_map=None):
if net is not None:
serialized_proto = None
i... | 4,208 | 28.851064 | 90 | py |
pytorch | pytorch-main/caffe2/python/net_printer_test.py |
from caffe2.python import net_printer
from caffe2.python.checkpoint import Job
from caffe2.python.net_builder import ops
from caffe2.python.task import Task, final_output, WorkspaceType
import unittest
def example_loop():
with Task():
total = ops.Const(0)
total_large = ops.Const(0)
to... | 3,190 | 30.91 | 77 | py |
pytorch | pytorch-main/caffe2/python/lstm_benchmark.py | ## @package lstm_benchmark
# Module caffe2.python.lstm_benchmark
from caffe2.proto import caffe2_pb2
from caffe2.python import workspace, core, utils, rnn_cell, model_helper
from caffe2.python import recurrent
import argparse
import numpy as np
import time
import logging
logging.basicConfig()
log = logging.getL... | 10,649 | 29.603448 | 79 | py |
pytorch | pytorch-main/caffe2/python/workspace_test.py | import errno
import os
import shutil
import tempfile
import unittest
from collections import namedtuple
from typing import List
import caffe2.python.hypothesis_test_util as htu
import hypothesis.strategies as st
import numpy as np
import torch
from torch import Tensor
from caffe2.proto import caffe2_pb2
from caffe2.py... | 34,526 | 35.966809 | 91 | py |
pytorch | pytorch-main/caffe2/python/functional_test.py |
import unittest
from caffe2.python import core
from hypothesis import given
import hypothesis.strategies as st
import caffe2.python.hypothesis_test_util as hu
from caffe2.python import workspace
from caffe2.python.functional import Functional
import numpy as np
@st.composite
def _tensor_splits(draw, add_axis=Fa... | 4,204 | 33.186992 | 91 | py |
pytorch | pytorch-main/caffe2/python/dyndep.py | ## @package dyndep
# Module caffe2.python.dyndep
import ctypes
import os
from threading import Lock
from caffe2.python import core, extension_loader
def InitOpsLibrary(name, trigger_lazy=True):
"""Loads a dynamic library that contains custom operators into Caffe2.
Since Caffe2 uses static variable regis... | 1,533 | 27.943396 | 77 | py |
pytorch | pytorch-main/caffe2/python/data_workers_test.py |
import numpy as np
import unittest
import time
from caffe2.python import workspace, model_helper
from caffe2.python import timeout_guard
import caffe2.python.data_workers as data_workers
def dummy_fetcher(fetcher_id, batch_size):
# Create random amount of values
n = np.random.randint(64) + 1
data = ... | 6,561 | 32.309645 | 83 | py |
pytorch | pytorch-main/caffe2/python/visualize.py | ## @package visualize
# Module caffe2.python.visualize
"""Functions that could be used to visualize Tensors.
This is adapted from the old-time iceberk package that Yangqing wrote... Oh gold
memories. Before decaf and caffe. Why iceberk? Because I was at Berkeley,
bears are vegetarian, and iceberg lettuce has layers of... | 6,291 | 34.75 | 83 | py |
pytorch | pytorch-main/caffe2/python/control_ops_grad.py | ## @package control_ops_grad
# Module caffe2.python.control_ops_grad
from caffe2.proto import caffe2_pb2
def gen_do_gradient(op, g_output):
"""
Generates gradient Do operator, given forward Do op and a list
of gradient blobs corresponding to forward op's outputs
Returns a gradient op and a list o... | 28,893 | 39.868458 | 84 | py |
pytorch | pytorch-main/caffe2/python/layer_test_util.py | ## @package layer_test_util
# Module caffe2.python.layer_test_util
from collections import namedtuple
from caffe2.python import (
core,
layer_model_instantiator,
layer_model_helper,
schema,
test_util,
workspace,
utils,
)
from caffe2.proto import caffe2_pb2
import numpy as np
# pyre-f... | 4,855 | 33.685714 | 80 | py |
pytorch | pytorch-main/caffe2/python/toy_regression_test.py | import numpy as np
import unittest
from caffe2.python import core, workspace, test_util
class TestToyRegression(test_util.TestCase):
def testToyRegression(self):
"""Tests a toy regression end to end.
The test code carries a simple toy regression in the form
y = 2.0 x1 + 1.5 x2 + 0.5
... | 2,822 | 42.430769 | 79 | py |
pytorch | pytorch-main/caffe2/python/optimizer_context.py | ## @package optimizer_context
# Module caffe2.python.optimizer_context
from caffe2.python import context
from caffe2.python.modifier_context import (
ModifierContext, UseModifierBase)
DEFAULT_OPTIM = 'DEFAULT'
class OptimizerContext(ModifierContext, context.DefaultManaged):
"""
provide context to a... | 1,462 | 26.092593 | 70 | py |
pytorch | pytorch-main/caffe2/python/gru_cell.py |
import functools
from caffe2.python import brew, rnn_cell
class GRUCell(rnn_cell.RNNCell):
def __init__(
self,
input_size,
hidden_size,
forget_bias, # Currently unused! Values here will be ignored.
memory_optimization,
drop_states=False,
linear_befor... | 5,113 | 28.560694 | 81 | py |
pytorch | pytorch-main/caffe2/python/layer_model_helper.py | # @package layer_model_helper
# Module caffe2.python.layer_model_helper
from caffe2.python import core, model_helper, schema, scope, utils, muji
from caffe2.python.modeling.parameter_info import (
ParameterInfo,
)
from caffe2.python.modeling.parameter_sharing import (
parameter_sharing_context,
)
from caff... | 29,256 | 37.853918 | 123 | py |
pytorch | pytorch-main/caffe2/python/_import_c_extension.py | ## @package _import_c_extension
# Module caffe2.python._import_c_extension
import atexit
import logging
import sys
from caffe2.python import extension_loader
# We will first try to load the gpu-enabled caffe2. If it fails, we will then
# attempt to load the cpu version. The cpu backend is the minimum required, so
# if... | 2,250 | 37.810345 | 79 | py |
pytorch | pytorch-main/caffe2/python/pipeline.py | ## @package pipeline
# Module caffe2.python.pipeline
from caffe2.python import core, queue_util
from caffe2.python.dataio import Reader, Writer
from caffe2.python.net_builder import NetBuilder, ops
from caffe2.python.schema import as_record, Field
from caffe2.python.task import Node, Task, TaskGroup
class Output... | 17,267 | 37.20354 | 82 | py |
pytorch | pytorch-main/caffe2/python/build.py |
import caffe2.python._import_c_extension as C
CAFFE2_NO_OPERATOR_SCHEMA = C.define_caffe2_no_operator_schema
build_options = C.get_build_options()
| 153 | 14.4 | 62 | py |
pytorch | pytorch-main/caffe2/python/optimizer.py | # @package optimizer
# Module caffe2.python.optimizer
import copy
import logging
from collections import defaultdict, namedtuple
from typing import Any, Dict
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, scope, utils, workspace
from caffe2.python.modeling import parameter_inf... | 83,387 | 34.199662 | 105 | py |
pytorch | pytorch-main/caffe2/python/modifier_context.py | # @package modifier_context
# Module caffe2.python.modifier_context
DEFAULT_MODIFIER = 'DEFAULT'
class ModifierContext:
"""
provide context to allow param_info to have different modifiers
"""
def __init__(self):
self._modifiers = {}
self._modifiers_list = []
def _rebuild_mo... | 1,756 | 24.838235 | 74 | py |
pytorch | pytorch-main/caffe2/python/schema.py | ## @package schema
# Module caffe2.python.schema
"""
Defines a minimal set of data types that allow to represent datasets with
arbitrary nested structure, including objects of variable length, such as
maps and lists.
This defines a columnar storage format for such datasets on top of caffe2
tensors. In terms of capacit... | 45,424 | 33.438969 | 115 | py |
pytorch | pytorch-main/caffe2/python/dataio_test.py |
from caffe2.python.dataio import (
CompositeReader,
CompositeReaderBuilder,
ReaderBuilder,
ReaderWithDelay,
ReaderWithLimit,
ReaderWithTimeLimit,
)
from caffe2.python.dataset import Dataset
from caffe2.python.db_file_reader import DBFileReader
from caffe2.python.pipeline import pipe
from ca... | 17,575 | 38.408072 | 89 | py |
pytorch | pytorch-main/caffe2/python/mint/app.py | ## @package app
# Module caffe2.python.mint.app
import argparse
import flask
import glob
import numpy as np
import nvd3
import os
import sys
# pyre-fixme[21]: Could not find module `tornado.httpserver`.
import tornado.httpserver
# pyre-fixme[21]: Could not find a module corresponding to import `tornado.wsgi`
import tor... | 5,743 | 29.231579 | 81 | py |
pytorch | pytorch-main/caffe2/python/predictor/predictor_exporter.py | ## @package predictor_exporter
# Module caffe2.python.predictor.predictor_exporter
from caffe2.proto import caffe2_pb2
from caffe2.proto import metanet_pb2
from caffe2.python import workspace, core, scope
from caffe2.python.predictor_constants import predictor_constants
import caffe2.python.predictor.serde as serd... | 10,002 | 36.74717 | 85 | py |
pytorch | pytorch-main/caffe2/python/predictor/predictor_py_utils.py | ## @package predictor_py_utils
# Module caffe2.python.predictor.predictor_py_utils
from caffe2.python import core, scope
def create_predict_net(predictor_export_meta):
"""
Return the input prediction net.
"""
# Construct a new net to clear the existing settings.
net = core.Net(predictor_export_m... | 6,534 | 28.840183 | 87 | py |
pytorch | pytorch-main/caffe2/python/predictor/mobile_exporter_test.py |
from caffe2.python.test_util import TestCase
from caffe2.python import workspace, brew
from caffe2.python.model_helper import ModelHelper
from caffe2.python.predictor import mobile_exporter
import numpy as np
class TestMobileExporter(TestCase):
def test_mobile_exporter(self):
model = ModelHelper(name=... | 4,851 | 35.481203 | 88 | py |
pytorch | pytorch-main/caffe2/python/predictor/serde.py | ## @package serde
# Module caffe2.python.predictor.serde
def serialize_protobuf_struct(protobuf_struct):
return protobuf_struct.SerializeToString()
def deserialize_protobuf_struct(serialized_protobuf, struct_type):
deser = struct_type()
deser.ParseFromString(serialized_protobuf)
return deser
| 317 | 17.705882 | 66 | py |
pytorch | pytorch-main/caffe2/python/predictor/predictor_exporter_test.py |
import tempfile
import unittest
import numpy as np
from caffe2.python import cnn, workspace, core
from caffe2.python.predictor_constants import predictor_constants as pc
import caffe2.python.predictor.predictor_exporter as pe
import caffe2.python.predictor.predictor_py_utils as pred_utils
from caffe2.proto import... | 8,655 | 34.917012 | 92 | py |
pytorch | pytorch-main/caffe2/python/predictor/predictor_test.py |
import unittest
import numpy as np
from caffe2.python import workspace, core
from caffe2.proto import caffe2_pb2
class TestPredictor(unittest.TestCase):
def setUp(self):
np.random.seed(1)
self.predict_net = self._predict_net
self.init_net = self._init_net
@property
def _pred... | 2,050 | 26.716216 | 72 | py |
pytorch | pytorch-main/caffe2/python/predictor/mobile_exporter.py | ## @package mobile_exporter
# Module caffe2.python.mobile_exporter
from caffe2.python import core, utils
from caffe2.proto import caffe2_pb2
import numpy as np
def add_tensor(net, name, blob):
''' Create an operator to store the tensor 'blob',
run the operator to put the blob to workspace.
ui... | 3,674 | 33.345794 | 78 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_sbn_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 3,110 | 36.481928 | 77 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_elementwise_sum_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 1,334 | 28.666667 | 76 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_pool_speed_test.py |
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace, test_util
@unittest.skipIf(not workspace.C.has_mkldnn, "Skipping as we do not have mkldnn.")
class TestMKLBasic(test_util.TestCase):
def testMaxPoolingSpeed(self):
# We randomly select a ... | 4,210 | 38.35514 | 94 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_relu_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 988 | 25.72973 | 79 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_concat_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do not have mkldn... | 1,173 | 24.521739 | 76 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_LRN_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 1,160 | 23.1875 | 76 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_elementwise_add_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 1,201 | 27.619048 | 76 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_sigmoid_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 833 | 24.272727 | 75 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_copy_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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
import caffe2.proto.caffe2_pb2 as pb2
@unittest.skipIf(not workspace.C.has_mkldnn,
... | 2,149 | 30.15942 | 77 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_LRN_speed_test.py |
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace, test_util
@unittest.skipIf(not workspace.C.has_mkldnn, "Skipping as we do not have mkldnn.")
class TestMKLBasic(test_util.TestCase):
def testLRNSpeed(self):
# We randomly select a shape t... | 3,182 | 38.7875 | 128 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_pool_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given, settings, assume
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,
"Sk... | 1,332 | 26.770833 | 70 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_speed_test.py |
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace, test_util
@unittest.skipIf(not workspace.C.has_mkldnn, "Skipping as we do not have mkldnn.")
class TestMKLBasic(test_util.TestCase):
def testReLUSpeed(self):
X = np.random.randn(128, 4096... | 3,079 | 37.024691 | 84 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_squeeze_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do not have mkldn... | 968 | 24.5 | 73 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_fc_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 927 | 23.421053 | 57 | py |
pytorch | pytorch-main/caffe2/python/mkl/rewrite_graph_test.py |
import unittest
import numpy as np
import copy
from hypothesis import given
import hypothesis.strategies as st
from caffe2.python.model_helper import ModelHelper
from caffe2.python.models import resnet
from caffe2.python import workspace, brew
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.m... | 7,889 | 29.820313 | 81 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_sbn_speed_test.py |
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace, test_util
@unittest.skipIf(not workspace.C.has_mkldnn, "Skipping as we do not have mkldnn.")
class TestMKLBasic(test_util.TestCase):
def testSpatialBNTestingSpeed(self):
input_channel = ... | 4,600 | 37.024793 | 101 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_fill_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do not have mkldnn.")
cl... | 1,019 | 25.842105 | 73 | py |
pytorch | pytorch-main/caffe2/python/mkl/rewrite_graph.py |
import copy
from caffe2.proto import caffe2_pb2
from caffe2.python import core
def rewrite_init_net_simple(net):
for op in net.op:
op.device_option.device_type = caffe2_pb2.IDEEP
def last_producer(ops, blob):
for (i, op) in reversed(list(enumerate(ops))):
if blob in op.output:
... | 8,433 | 38.046296 | 82 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_conv_op_test.py |
import unittest
import hypothesis.strategies as st
from hypothesis import given
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 as we do no... | 1,684 | 30.203704 | 84 | py |
pytorch | pytorch-main/caffe2/python/mkl/mkl_fc_speed_test.py |
import unittest
import numpy as np
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace, test_util
@unittest.skipIf(not workspace.C.has_mkldnn, "Skipping as we do not have mkldnn.")
class TestMKLBasic(test_util.TestCase):
def testFCSpeed(self):
# We randomly select a shape to... | 3,849 | 38.690722 | 82 | py |
pytorch | pytorch-main/caffe2/python/benchmarks/concat_benchmark.py | import argparse
import numpy as np
from caffe2.python import core, workspace
def benchmark_concat(num_inputs, input_dim, axis, add_axis, iterations):
input_names = [f"input{i}" for i in range(num_inputs)]
for n in input_names:
workspace.FeedBlob(n, np.random.randn(*input_dim).astype(np.float32))
... | 1,244 | 37.90625 | 83 | py |
pytorch | pytorch-main/caffe2/python/benchmarks/fused_rowwise_nbit_conversion_bench.py |
import argparse
import numpy as np
from caffe2.python import core, workspace
def main(bit_rate):
# uncomment for debugging
# np.random.seed(0)
batchsize = 10 * 1000
blocksize = 64
print(batchsize, blocksize)
input_data = np.random.rand(batchsize, blocksize).astype(np.float32)
workspace... | 1,330 | 25.098039 | 72 | py |
pytorch | pytorch-main/caffe2/python/benchmarks/sparse_normalize_benchmark.py | import argparse
import datetime
# import hypothesis.strategies as st
import numpy as np
from caffe2.python import core, workspace
def benchmark_sparse_normalize(
categorical_limit,
embedding_size,
average_len,
batch_size,
iterations,
flush_cache,
fp16,
):
print("Preparing lookup table... | 3,794 | 30.106557 | 86 | py |
pytorch | pytorch-main/caffe2/python/benchmarks/sparse_lengths_sum_nbit_benchmark.py |
import argparse
import datetime
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core, workspace
def benchmark_sparse_lengths_sum(
categorical_limit,
embedding_size,
average_len,
batch_size,
iterations,
flush_cache,
bit_rate=st.sampled_from([2, 4]),
):
... | 3,578 | 29.330508 | 87 | py |
pytorch | pytorch-main/caffe2/python/serialized_test/coverage.py |
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace
import os
import tempfile
from zipfile import ZipFile
'''
Generates a document in markdown format summrizing the coverage of serialized
testing. The document lives in
`caffe2/python/serialized_test/SerializedTestCoverage.md`
'''
OpSche... | 3,809 | 31.564103 | 80 | py |
pytorch | pytorch-main/caffe2/python/serialized_test/serialized_test_util.py |
import inspect
import os
import shutil
import sys
import tempfile
import threading
from contextlib import contextmanager
from zipfile import ZipFile
import argparse
import hypothesis as hy
import numpy as np
import caffe2.python.hypothesis_test_util as hu
from caffe2.proto import caffe2_pb2
from caffe2.python impo... | 9,798 | 31.772575 | 100 | py |
pytorch | pytorch-main/caffe2/python/trt/test_pt_onnx_trt.py | ###################################################################################################
# ATTENTION! This test will most probably fail if you install TensorRT 6.0.1 only.
# That's because it's shipped with older version of ONNX parser not supporting some
# required features. To make it work please use new v... | 7,636 | 38.984293 | 141 | py |
pytorch | pytorch-main/caffe2/python/trt/test_trt.py |
from caffe2.proto import caffe2_pb2
from caffe2.python import core, workspace
import onnx
import onnx.defs
from onnx.helper import make_node, make_graph, make_tensor_value_info, make_model
from onnx.backend.base import namedtupledict
from caffe2.python.models.download import ModelDownloader
import caffe2.python.on... | 11,308 | 39.389286 | 122 | py |
pytorch | pytorch-main/caffe2/python/trt/transform.py | ## @package onnx
#Module caffe2.python.trt.transform
"""
TensorRT related transformation
Note that ONNX-TRT enforce an NCHW input!
"""
from caffe2.proto import caffe2_pb2
from caffe2.python import workspace
import caffe2.python._import_c_extension as C
import numpy as np
def _dim_values_to_list(dim_values):
... | 3,252 | 28.844037 | 92 | py |
pytorch | pytorch-main/caffe2/python/examples/char_rnn.py | ## @package char_rnn
# Module caffe2.python.examples.char_rnn
from caffe2.python import core, workspace, model_helper, utils, brew
from caffe2.python.rnn_cell import LSTM
from caffe2.proto import caffe2_pb2
from caffe2.python.optimizer import build_sgd
import argparse
import logging
import numpy as np
from datet... | 9,815 | 34.436823 | 79 | py |
pytorch | pytorch-main/caffe2/python/examples/imagenet_trainer.py | # Module caffe2.python.examples.resnet50_trainer
import argparse
import logging
import numpy as np
import time
import os
from caffe2.python import core, workspace, experiment_util, data_parallel_model
from caffe2.python import dyndep, optimizer
from caffe2.python import timeout_guard, model_helper, brew
from caffe2.pr... | 27,287 | 36.535076 | 86 | py |
pytorch | pytorch-main/caffe2/python/examples/lmdb_create_example.py | ## @package lmdb_create_example
# Module caffe2.python.examples.lmdb_create_example
import argparse
import numpy as np
import lmdb
from caffe2.proto import caffe2_pb2
from caffe2.python import workspace, model_helper
'''
Simple example to create an lmdb database of random image data and labels.
This can be used ... | 3,036 | 27.12037 | 74 | py |
pytorch | pytorch-main/caffe2/python/helpers/fc.py | ## @package fc
# Module caffe2.python.helpers.fc
from caffe2.python import core
from caffe2.python.modeling import initializers
from caffe2.python.modeling.parameter_info import ParameterTags
def _FC_or_packed_FC(
model, op_call, blob_in, blob_out, dim_in, dim_out, weight_init=None,
bias_init=None, W... | 6,405 | 31.353535 | 80 | py |
pytorch | pytorch-main/caffe2/python/helpers/pooling.py | ## @package pooling
# Module caffe2.python.helpers.pooling
## @package fc
# Module caffe2.python.helpers.pooling
def max_pool(model, blob_in, blob_out, use_cudnn=False, order="NCHW", **kwargs):
"""Max pooling"""
if use_cudnn:
kwargs['engine'] = 'CUDNN'
return model.net.MaxPool(blob_in, blob_ou... | 924 | 22.717949 | 80 | py |
pytorch | pytorch-main/caffe2/python/helpers/quantization.py | # @package quantization
# Module caffe2.python.helpers.quantization
def fused_8bit_rowwise_quantized_to_float(
model, blob_in, blob_out
):
"""Fused8BitRowwiseQuantizedToFloat"""
return model.net.Fused8BitRowwiseQuantizedToFloat(blob_in, blob_out)
| 261 | 25.2 | 72 | py |
pytorch | pytorch-main/caffe2/python/helpers/nonlinearity.py | ## @package nonlinearity
# Module caffe2.python.helpers.nonlinearity
from caffe2.python import core
def prelu(model, blob_in, blob_out, num_channels=1, slope_init=None,
**kwargs):
"""PRelu"""
slope_init = (
slope_init if slope_init else ('ConstantFill', {'value': 0.25}))
if model.in... | 1,145 | 25.045455 | 76 | py |
pytorch | pytorch-main/caffe2/python/helpers/elementwise_linear.py | ## @package elementwise_linear
# Module caffe2.python.helpers.elementwise_linear
from caffe2.python import core
from caffe2.python.modeling.parameter_info import ParameterTags
def _elementwise_linear(
model, op_call, blob_in, blob_out, dim,
weight_init=None, bias_init=None, **kwargs
):
"""Elementwise... | 1,385 | 28.489362 | 66 | py |
pytorch | pytorch-main/caffe2/python/helpers/array_helpers.py | ## @package arra_helpers
# Module caffe2.python.helpers.array_helpers
def concat(model, blobs_in, blob_out, **kwargs):
"""Depth Concat."""
if kwargs.get('order') and kwargs.get('axis'):
# The backend throws an error if both are given
kwargs.pop('order')
return model.net.Concat(
... | 648 | 23.961538 | 71 | py |
pytorch | pytorch-main/caffe2/python/helpers/tools.py | ## @package tools
# Module caffe2.python.helpers.tools
def image_input(
model, blob_in, blob_out, order="NCHW", use_gpu_transform=False, **kwargs
):
assert 'is_test' in kwargs, "Argument 'is_test' is required"
if order == "NCHW":
if (use_gpu_transform):
kwargs['use_gpu_transform'] ... | 1,089 | 30.142857 | 79 | py |
pytorch | pytorch-main/caffe2/python/helpers/dropout.py | ## @package dropout
# Module caffe2.python.helpers.dropout
def dropout(model, blob_in, blob_out, use_cudnn=False, **kwargs):
"""dropout"""
if use_cudnn:
kwargs['engine'] = 'CUDNN'
else:
kwargs['engine'] = 'DEFAULT'
assert 'is_test' in kwargs, "Argument 'is_test' is required"
re... | 412 | 21.944444 | 67 | py |
pytorch | pytorch-main/caffe2/python/helpers/control_ops.py | ## @package control_ops
# Module caffe2.python.helpers.control_ops
from caffe2.python.control_ops_util import add_if_op, add_while_op
def cond(model, cond_blob, external_blobs, then_model, else_model=None):
"""Condition"""
add_if_op(
model.net,
cond_blob,
external_blobs,
t... | 625 | 20.586207 | 72 | py |
pytorch | pytorch-main/caffe2/python/helpers/db_input.py | ## @package db_input
# Module caffe2.python.helpers.db_input
def db_input(model, blobs_out, batch_size, db, db_type):
dbreader_name = "dbreader_" + db
dbreader = model.param_init_net.CreateDB(
[],
dbreader_name,
db=db,
db_type=db_type,
)
return model.net.TensorProtos... | 381 | 20.222222 | 56 | py |
pytorch | pytorch-main/caffe2/python/helpers/conv.py | ## @package conv
# Module caffe2.python.helpers.conv
from caffe2.python import core
from caffe2.python.modeling import initializers
from caffe2.python.modeling.parameter_info import ParameterTags
def _ConvBase(
model,
is_nd,
blob_in,
blob_out,
dim_in,
dim_out,
kernel,
weight_init=N... | 10,396 | 27.641873 | 80 | py |
pytorch | pytorch-main/caffe2/python/helpers/normalization.py | ## @package normalization
# Module caffe2.python.helpers.normalization
from caffe2.python import scope
from caffe2.python.modeling.parameter_info import ParameterTags
from caffe2.proto import caffe2_pb2
from caffe2.python.modeling import initializers
def lrn(model, blob_in, blob_out, order="NCHW", use_cudnn=Fals... | 10,891 | 32.721362 | 98 | py |
pytorch | pytorch-main/caffe2/python/helpers/train.py | ## @package train
# Module caffe2.python.helpers.train
from caffe2.python import core, scope
from caffe2.proto import caffe2_pb2
def _get_weights(model, namescope=None):
if namescope is None:
namescope = scope.CurrentNameScope()
if namescope == '':
return model.weights[:]
else:
... | 2,192 | 26.759494 | 77 | py |
pytorch | pytorch-main/caffe2/python/helpers/algebra.py | ## @package algebra
# Module caffe2.python.helpers.algebra
def transpose(model, blob_in, blob_out, use_cudnn=False, **kwargs):
"""Transpose."""
if use_cudnn:
kwargs['engine'] = 'CUDNN'
return model.net.Transpose(blob_in, blob_out, **kwargs)
def sum(model, blob_in, blob_out, **kwargs):
""... | 1,296 | 25.469388 | 83 | py |
pytorch | pytorch-main/caffe2/python/models/download.py | ## @package download
# Module caffe2.python.models.download
import argparse
import os
import sys
import signal
import re
import json
from caffe2.proto import caffe2_pb2
# Import urllib
from urllib.error import HTTPError, URLError
import urllib.request as urllib
# urllib requires more work to deal with a redirect... | 8,017 | 36.12037 | 88 | py |
pytorch | pytorch-main/caffe2/python/models/resnet.py | ## @package resnet
# Module caffe2.python.models.resnet
from caffe2.python import brew
import logging
'''
Utility for creating ResNe(X)t
"Deep Residual Learning for Image Recognition" by He, Zhang et. al. 2015
"Aggregated Residual Transformations for Deep Neural Networks" by Xie et. al. 2016
'''
class ResNetBui... | 11,972 | 26.524138 | 85 | py |
pytorch | pytorch-main/caffe2/python/models/__sym_init__.py |
import os
from caffe2.proto import caffe2_pb2
def _parseFile(filename):
out_net = caffe2_pb2.NetDef()
# TODO(bwasti): A more robust handler for pathnames.
dir_path = os.path.dirname(__file__)
with open('{dir_path}/{filename}'.format(dir_path=dir_path,
f... | 494 | 22.571429 | 76 | py |
pytorch | pytorch-main/caffe2/python/models/imagenet_trainer_test_utils.py |
import numpy as np
import time
from caffe2.python import workspace, cnn, memonger, core
def has_blob(proto, needle):
for op in proto.op:
for inp in op.input:
if inp == needle:
return True
for outp in op.output:
if outp == needle:
return ... | 5,755 | 27.636816 | 70 | py |
pytorch | pytorch-main/caffe2/python/models/shufflenet.py | # Module caffe2.python.models.shufflenet
from caffe2.python import brew
"""
Utilitiy for creating ShuffleNet
"ShuffleNet V2: Practical Guidelines for EfficientCNN Architecture Design" by Ma et. al. 2018
"""
OUTPUT_CHANNELS = {
'0.5x': [24, 48, 96, 192, 1024],
'1.0x': [24, 116, 232, 464, 1024],
'1.5x... | 7,832 | 38.361809 | 93 | py |
pytorch | pytorch-main/caffe2/python/models/resnet_test.py |
import numpy as np
import caffe2.python.models.resnet as resnet
import hypothesis.strategies as st
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.models.imagenet_trainer_test_utils as utils
class ResnetMemongerTest(hu.HypothesisTestCase):
@given(w... | 2,008 | 30.888889 | 83 | py |
pytorch | pytorch-main/caffe2/python/models/shufflenet_test.py |
import numpy as np
import caffe2.python.models.shufflenet as shufflenet
import hypothesis.strategies as st
from hypothesis import given, settings
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.models.imagenet_trainer_test_utils as utils
class ShufflenetMemongerTest(hu.HypothesisTestCase):
... | 2,056 | 32.177419 | 83 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/seq2seq_util.py | ## @package seq2seq_util
# Module caffe2.python.examples.seq2seq_util
""" A bunch of util functions to build Seq2Seq models with Caffe2."""
import collections
import caffe2.proto.caffe2_pb2 as caffe2_pb2
from caffe2.python import attention, core, rnn_cell, brew
PAD_ID = 0
PAD = '<PAD>'
GO_ID = 1
GO = '<GO>'
EO... | 20,187 | 29.041667 | 80 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/seq2seq_model_helper.py | ## @package seq2seq_model_helper
# Module caffe2.python.models.seq2seq.seq2seq_model_helper
from caffe2.python import scope
from caffe2.python.model_helper import ModelHelper
class Seq2SeqModelHelper(ModelHelper):
def __init__(self, init_params=True, **kwargs):
arg_scope = {
'use_cudnn':... | 2,591 | 30.228916 | 84 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/seq2seq_model_helper_test.py |
from caffe2.python.models.seq2seq import seq2seq_model_helper
from caffe2.python import scope, test_util
class Seq2SeqModelHelperTest(test_util.TestCase):
def testConstuctor(self):
model_name = 'TestModel'
m = seq2seq_model_helper.Seq2SeqModelHelper(name=model_name)
self.assertEqual(... | 1,838 | 24.901408 | 73 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/translate.py | ## @package translate
# Module caffe2.python.models.seq2seq.translate
from abc import ABCMeta, abstractmethod
import argparse
import logging
import numpy as np
import sys
from caffe2.python import core, rnn_cell, workspace
from caffe2.python.models.seq2seq.beam_search import BeamSearchForwardOnly
from caffe2.pyth... | 24,073 | 35.754198 | 81 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/beam_search.py | ## @package beam_search
# Module caffe2.python.models.seq2seq.beam_search
from collections import namedtuple
from caffe2.python import core
import caffe2.python.models.seq2seq.seq2seq_util as seq2seq_util
from caffe2.python.models.seq2seq.seq2seq_model_helper import Seq2SeqModelHelper
class BeamSearchForwardOnly... | 17,028 | 33.47166 | 80 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/seq2seq_beam_search_test.py |
import numpy as np
import os
import tempfile
from caffe2.python import test_util, workspace
import caffe2.python.models.seq2seq.seq2seq_util as seq2seq_util
from caffe2.python.models.seq2seq.train import Seq2SeqModelCaffe2
from caffe2.python.models.seq2seq.translate import (
Seq2SeqModelCaffe2EnsembleDecoder,... | 6,376 | 28.523148 | 80 | py |
pytorch | pytorch-main/caffe2/python/models/seq2seq/train.py | ## @package train
# Module caffe2.python.models.seq2seq.train
import argparse
import collections
import logging
import math
import numpy as np
import random
import time
import sys
import os
import caffe2.proto.caffe2_pb2 as caffe2_pb2
from caffe2.python import core, workspace, data_parallel_model
import caffe2.py... | 27,510 | 34.728571 | 81 | py |
pytorch | pytorch-main/caffe2/python/rnn/rnn_cell_test_util.py |
from caffe2.python import workspace, scope
from caffe2.python.model_helper import ModelHelper
import numpy as np
def sigmoid(x):
return 1.0 / (1.0 + np.exp(-x))
def tanh(x):
return 2.0 * sigmoid(2.0 * x) - 1
def _prepare_rnn(
t, n, dim_in, create_rnn, outputs_with_grads,
forget_bias, memory_... | 2,132 | 27.065789 | 74 | py |
pytorch | pytorch-main/caffe2/python/rnn/lstm_comparison.py |
from caffe2.python import workspace, core, lstm_benchmark, utils
from copy import copy
@utils.debug
def Compare(args):
results = []
num_iters = 1000
args.gpu = True
with core.DeviceScope(core.DeviceOption(workspace.GpuDeviceType, 0)):
for batch_size in [64, 128, 256]:
for seq_le... | 2,076 | 34.20339 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/ctc_beam_search_decoder_op_test.py |
from caffe2.python import core
from collections import defaultdict, Counter
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
DEFAULT_BEAM... | 5,197 | 36.666667 | 98 | py |
pytorch | pytorch-main/caffe2/python/operator_test/elementwise_logical_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
from hypothesis import given, settings
import hypothesis.strategies as st
import numpy as np
import unittest
def mux(select, left, right):
return [np.vectorize(la... | 4,617 | 32.463768 | 80 | py |
pytorch | pytorch-main/caffe2/python/operator_test/specialized_segment_ops_test.py |
import unittest
from caffe2.proto import caffe2_pb2
from caffe2.python import core
import caffe2.python.hip_test_util as hiputl
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
from hypothesis import given, assume, settings
class TestSpecializedSegmentOps(hu.Hyp... | 11,775 | 34.46988 | 93 | py |
pytorch | pytorch-main/caffe2/python/operator_test/integral_image_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
from hypothesis import given, settings
import numpy as np
class TestIntegralImageOps(serial.SerializedTestCase):
@given(batch_s... | 3,419 | 35 | 83 | py |
pytorch | pytorch-main/caffe2/python/operator_test/listwise_l2r_operator_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 TestListwiseL2rOps(hu.HypothesisTestCase):
def ref_lambda_rank_loss(
self, y, r, use_ndcg_as_loss, use_idcg_normalization, us... | 8,740 | 34.971193 | 86 | py |
pytorch | pytorch-main/caffe2/python/operator_test/alias_with_name_test.py | #!/usr/bin/env python3
import caffe2.python.hypothesis_test_util as hu
import hypothesis.strategies as st
import numpy as np
from caffe2.python import core, utils
from hypothesis import given
class TestAliasWithNameOp(hu.HypothesisTestCase):
@given(
shape=st.lists(st.integers(0, 5), min_size=1, max_size=... | 938 | 28.34375 | 80 | py |
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