repo stringlengths 1 152 ⌀ | file stringlengths 14 221 | code stringlengths 501 25k | file_length int64 501 25k | avg_line_length float64 20 99.5 | max_line_length int64 21 134 | extension_type stringclasses 2
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null | pytorch-main/caffe2/operators/sparse_normalize_op.h | #pragma once
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T, class Context>
class TORCH_API SparseNormalizeOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit SparseNormalizeOp(Args&&... args)... | 834 | 23.558824 | 74 | h |
null | pytorch-main/caffe2/operators/sparse_to_dense_mask_op.h | #ifndef CAFFE2_OPERATORS_SPARSE_TO_DENSE_MASK_OP_H_
#define CAFFE2_OPERATORS_SPARSE_TO_DENSE_MASK_OP_H_
#include <algorithm>
#include <unordered_map>
#include <vector>
#include "caffe2/core/context.h"
#include "caffe2/core/export_caffe2_op_to_c10.h"
#include <c10/util/irange.h>
#include "caffe2/core/operator.h"
#inclu... | 10,051 | 32.395349 | 80 | h |
null | pytorch-main/caffe2/operators/sparse_to_dense_op.h | #ifndef CAFFE2_OPERATORS_SPARSE_TO_DENSE_OP_H_
#define CAFFE2_OPERATORS_SPARSE_TO_DENSE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
#include "c10/util/irange.h"
namespace caffe2 {
template <class Context>
class SparseToDenseOp final : public Operator<Contex... | 4,010 | 30.093023 | 95 | h |
null | pytorch-main/caffe2/operators/spatial_batch_norm_op.h | #ifndef CAFFE2_OPERATORS_SPATIAL_BATCH_NORM_OP_H_
#define CAFFE2_OPERATORS_SPATIAL_BATCH_NORM_OP_H_
#include <algorithm>
#include <array>
#include <functional>
#include <limits>
#include <string>
#include <vector>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/eigen_utils.h"... | 15,176 | 30.42236 | 80 | h |
null | pytorch-main/caffe2/operators/spatial_softmax_with_loss_op.h | #ifndef SPATIAL_SOFTMAX_WITH_LOSS_OP_H_
#define SPATIAL_SOFTMAX_WITH_LOSS_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename T, class Context>
class SpatialSoftmaxWithLossOp final : public Oper... | 2,182 | 29.746479 | 80 | h |
null | pytorch-main/caffe2/operators/square_root_divide_op.h | #ifndef CAFFE2_OPERATORS_SQUARE_ROOT_DIVIDE_OP_H_
#define CAFFE2_OPERATORS_SQUARE_ROOT_DIVIDE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
#include "c10/util/irange.h"
namespace caffe2 {
template <class Context>
class SquareRootDivideOp final : public Operat... | 1,896 | 28.184615 | 80 | h |
null | pytorch-main/caffe2/operators/stats_put_ops.h | #include <limits>
#include "caffe2/core/operator.h"
#include "caffe2/core/stats.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/types.h"
namespace caffe2 {
template <typename T>
struct TemplatePutOp : public Operator<CPUContext> {
explicit TemplatePutOp(const OperatorDef& operator_def, Workspace* ws)
... | 2,813 | 28.010309 | 77 | h |
null | pytorch-main/caffe2/operators/stop_gradient.h | #ifndef CAFFE2_OPERATORS_STOP_GRADIENT_H_
#define CAFFE2_OPERATORS_STOP_GRADIENT_H_
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class StopGradientOp : public Operator<Context> {
public:
USE_SIMPLE_CTOR_DTOR(StopGradientOp)
USE_OPERATOR_CONTEXT_FUNCTIONS;
bool RunOnDevice() ov... | 548 | 20.115385 | 49 | h |
null | pytorch-main/caffe2/operators/string_ops.h | #ifndef CAFFE2_OPERATORS_STRING_OPS_H_
#define CAFFE2_OPERATORS_STRING_OPS_H_
#include "caffe2/core/operator.h"
#include "caffe2/operators/elementwise_ops.h"
namespace caffe2 {
/**
* ForEach is a unary functor that forwards each element of the input array
* into the elementwise Functor provided, and gathers the re... | 2,075 | 25.615385 | 77 | h |
null | pytorch-main/caffe2/operators/stump_func_op.h | /**
* 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 ... | 2,112 | 28.347222 | 79 | h |
null | pytorch-main/caffe2/operators/summarize_op.h | #ifndef CAFFE2_OPERATORS_SUMMARIZE_OP_H_
#define CAFFE2_OPERATORS_SUMMARIZE_OP_H_
#include <fstream>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
constexpr char kSummaryzeOpExtension[] = ".summary";
template <typename T, class Context>
class S... | 1,884 | 29.403226 | 75 | h |
null | pytorch-main/caffe2/operators/swish_op.h | #ifndef CAFFE2_OPERATORS_SWISH_OP_H_
#define CAFFE2_OPERATORS_SWISH_OP_H_
#include "caffe2/operators/elementwise_ops.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <class Context>
struct SwishFunctor {
template <typename T>
bool operator()(const int N, const T* X, T* Y, Context* context) const;
};... | 772 | 20.472222 | 76 | h |
null | pytorch-main/caffe2/operators/tensor_protos_db_input.h | #ifndef CAFFE2_OPERATORS_TENSOR_PROTOS_DB_INPUT_H_
#define CAFFE2_OPERATORS_TENSOR_PROTOS_DB_INPUT_H_
#include "caffe2/core/db.h"
#include "caffe2/operators/prefetch_op.h"
#include "c10/util/irange.h"
#include <iostream>
#include <mutex>
namespace caffe2 {
template <class Context>
class TensorProtosDBInput final : ... | 3,697 | 32.926606 | 79 | h |
null | pytorch-main/caffe2/operators/text_file_reader_utils.h | #ifndef CAFFE2_OPERATORS_TEXT_FILE_READER_UTILS_H
#define CAFFE2_OPERATORS_TEXT_FILE_READER_UTILS_H
#include <memory>
#include <string>
#include <vector>
#include "caffe2/core/common.h"
namespace caffe2 {
struct TORCH_API Token {
int startDelimId;
const char* start;
const char* end;
};
class TORCH_API Tokeni... | 2,922 | 22.764228 | 77 | h |
null | pytorch-main/caffe2/operators/thresholded_relu_op.h | #ifndef CAFFE2_OPERATORS_THRESHOLDED_RELU_OP_H_
#define CAFFE2_OPERATORS_THRESHOLDED_RELU_OP_H_
#include "caffe2/core/common_omp.h"
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
template <typename T, class Context>
class ThresholdedReluOp final... | 1,137 | 23.73913 | 66 | h |
null | pytorch-main/caffe2/operators/tile_op.h | #ifndef CAFFE2_OPERATORS_TILE_OP_H_
#define CAFFE2_OPERATORS_TILE_OP_H_
#include <array>
#include <string>
#include <type_traits>
#include <vector>
#include "caffe2/core/common_omp.h"
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/eigen_utils... | 8,776 | 31.628253 | 78 | h |
null | pytorch-main/caffe2/operators/transpose_op.h | #ifndef CAFFE2_OPERATORS_TRANSPOSE_H_
#define CAFFE2_OPERATORS_TRANSPOSE_H_
#include <algorithm>
#include <vector>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/math.h"
#include "c10/util/irange.h"
namespace caffe2 {
template <class Context>
class TransposeOp : public Ope... | 2,086 | 25.75641 | 80 | h |
null | pytorch-main/caffe2/operators/tt_linear_op.h | #ifndef CAFFE2_OPERATORS_TT_LINEAR_OP_H_
#define CAFFE2_OPERATORS_TT_LINEAR_OP_H_
#ifdef CAFFE2_USE_MKL
#include <mkl.h>
#endif // CAFFE2_USE_MKL
#include "Eigen/Core"
#include "Eigen/Dense"
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/eigen_utils.h"
#include "caffe2/utils... | 6,474 | 32.035714 | 80 | h |
null | pytorch-main/caffe2/operators/unique_ops.h | /**
* 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 ... | 1,666 | 26.327869 | 79 | h |
null | pytorch-main/caffe2/operators/unsafe_coalesce.h | #ifndef CAFFE2_OPERATORS_UNSAFE_COALESCE_OP_H_
#define CAFFE2_OPERATORS_UNSAFE_COALESCE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/export_caffe2_op_to_c10.h"
#include <c10/util/irange.h>
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class UnsafeCoalesceOp final : pu... | 2,533 | 34.690141 | 107 | h |
null | pytorch-main/caffe2/operators/upsample_op.h | /**
* 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 ... | 2,246 | 28.181818 | 75 | h |
null | pytorch-main/caffe2/operators/variable_length_sequence_padding.h | #pragma once
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/utils/eigen_utils.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
namespace detail {
template <typename T, typename Context>
void VariableLengthSequencePadding(
int N,
int B,
int M,
T* X,
const i... | 1,386 | 23.333333 | 77 | h |
null | pytorch-main/caffe2/operators/weighted_multi_sampling_op.h | #pragma once
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class WeightedMultiSamplingOp : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTIONS;
template <class... Args>
explicit WeightedMultiSamplingOp(Args&&... args)
: Opera... | 602 | 21.333333 | 74 | h |
null | pytorch-main/caffe2/operators/weighted_sample_op.h | // Copyright 2004-present Facebook. All Rights Reserved.
#ifndef CAFFE2_OPERATORS_WEIGHTEDSAMPLE_OP_H_
#define CAFFE2_OPERATORS_WEIGHTEDSAMPLE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <typename... | 739 | 22.125 | 57 | h |
null | pytorch-main/caffe2/operators/while_op.h | #ifndef CAFFE2_OPERATORS_WHILE_OP_H_
#define CAFFE2_OPERATORS_WHILE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
template <class Context>
class WhileOp final : public Operator<Context> {
public:
explicit WhileOp(const OperatorDef& ope... | 1,961 | 25.876712 | 77 | h |
null | pytorch-main/caffe2/operators/hip/activation_ops_miopen.h | #ifndef CAFFE2_OPERATORS_ACTIVATION_OPS_MIOPEN_H_
#define CAFFE2_OPERATORS_ACTIVATION_OPS_MIOPEN_H_
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/hip/miopen_wrapper.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/types.h"
namespace caffe2 {
class MIOPENActi... | 4,678 | 29.782895 | 78 | h |
null | pytorch-main/caffe2/operators/quantized/int8_add_op.h | #ifndef CAFFE2_OPERATORS_INT8_ADD_OP_H_
#define CAFFE2_OPERATORS_INT8_ADD_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
template <Activation Ac... | 3,630 | 29.512605 | 82 | h |
null | pytorch-main/caffe2/operators/quantized/int8_average_pool_op.h | #ifndef CAFFE2_OPERATORS_INT8_AVERAGE_POOL_OP_H_
#define CAFFE2_OPERATORS_INT8_AVERAGE_POOL_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/operators/quantized/int8_utils... | 5,814 | 33.408284 | 79 | h |
null | pytorch-main/caffe2/operators/quantized/int8_channel_shuffle_op.h | #ifndef CAFFE2_OPERATORS_INT8_CHANNEL_SHUFFLE_OP_H_
#define CAFFE2_OPERATORS_INT8_CHANNEL_SHUFFLE_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/operators/quantized/int8... | 3,459 | 31.037037 | 79 | h |
null | pytorch-main/caffe2/operators/quantized/int8_concat_op.h | #ifndef CAFFE2_OPERATORS_INT8_CONCAT_OP_H_
#define CAFFE2_OPERATORS_INT8_CONCAT_OP_H_
#include <c10/util/irange.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int8... | 3,175 | 33.150538 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_conv_op.h | #ifndef CAFFE2_OPERATORS_INT8_CONV_OP_H_
#define CAFFE2_OPERATORS_INT8_CONV_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/conv_op_shared.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/o... | 6,290 | 33.95 | 77 | h |
null | pytorch-main/caffe2/operators/quantized/int8_conv_transpose_op.h | #ifndef CAFFE2_OPERATORS_INT8_CONV_TRANSPOSE_OP_H_
#define CAFFE2_OPERATORS_INT8_CONV_TRANSPOSE_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/conv_op_shared.h"
#include "caffe2/operators/conv_transpose_unpo... | 5,947 | 33.183908 | 78 | h |
null | pytorch-main/caffe2/operators/quantized/int8_dequantize_op.h | #ifndef CAFFE2_OPERATORS_INT8_DEQUANTIZE_OP_H_
#define CAFFE2_OPERATORS_INT8_DEQUANTIZE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
#include <c10/util/irange.h>
namespace caffe2 {
namespace int8 {
n... | 1,185 | 20.563636 | 64 | h |
null | pytorch-main/caffe2/operators/quantized/int8_fc_op.h | #ifndef CAFFE2_OPERATORS_INT8_FC_OP_H_
#define CAFFE2_OPERATORS_INT8_FC_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/conv_op_shared.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {... | 4,551 | 31.748201 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_flatten_op.h | #ifndef CAFFE2_OPERATORS_INT8_FLATTEN_OP_H_
#define CAFFE2_OPERATORS_INT8_FLATTEN_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int8FlattenOp : public Operator... | 1,421 | 28.020408 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_given_tensor_fill_op.h | #ifndef CAFFE2_OPERATORS_INT8_GIVEN_TENSOR_FILL_OP_H_
#define CAFFE2_OPERATORS_INT8_GIVEN_TENSOR_FILL_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/filler_op.h"
#include "caffe2/utils/cast.h"
#in... | 3,976 | 31.333333 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_leaky_relu_op.h | #ifndef CAFFE2_OPERATORS_INT8_LEAKY_RELU_OP_H_
#define CAFFE2_OPERATORS_INT8_LEAKY_RELU_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int... | 3,658 | 30.273504 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_max_pool_op.h | #ifndef CAFFE2_OPERATORS_INT8_MAX_POOL_OP_H_
#define CAFFE2_OPERATORS_INT8_MAX_POOL_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/conv_pool_op_base.h"
#include "caffe2/operators/quantized/int8_utils.h"
nam... | 3,447 | 29.785714 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_quantize_op.h | #ifndef CAFFE2_OPERATORS_INT8_QUANTIZE_OP_H_
#define CAFFE2_OPERATORS_INT8_QUANTIZE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_simd.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
nam... | 2,996 | 30.882979 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_relu_op.h | #ifndef CAFFE2_OPERATORS_INT8_RELU_OP_H_
#define CAFFE2_OPERATORS_INT8_RELU_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int8ReluOp fina... | 3,060 | 29.306931 | 77 | h |
null | pytorch-main/caffe2/operators/quantized/int8_reshape_op.h | #ifndef CAFFE2_OPERATORS_INT8_RESHAPE_OP_H_
#define CAFFE2_OPERATORS_INT8_RESHAPE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
#include "caffe2/operators/reshape_op.h"
namespace caffe2 {
namespace int8... | 1,416 | 27.918367 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_resize_nearest_op.h | #ifndef CAFFE2_OPERATORS_INT8_RESIZE_NEAREST_OP_H_
#define CAFFE2_OPERATORS_INT8_RESIZE_NEAREST_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
#include <c10/util/irange.h>
namespace caffe2 {
namespace in... | 2,685 | 30.97619 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_roi_align_op.h | #ifndef CAFFE2_OPERATORS_INT8_ROI_ALIGN_OP_H_
#define CAFFE2_OPERATORS_INT8_ROI_ALIGN_OP_H_
#include "caffe2/core/common.h"
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/operator_schema.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/... | 11,524 | 31.013889 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_sigmoid_op.h | #ifndef CAFFE2_INT8_SIGMOID_OP_H_
#define CAFFE2_INT8_SIGMOID_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int8SigmoidOp final : public O... | 3,297 | 29.537037 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_simd.h | #pragma once
// We want to allow 128-bit wide SIMD if either NEON is available (as
// detected by GEMMLOWP_NEON), or whether SSE4.2 and Clang is
// available (in which case we will use the neon_sse.h library to
// share source between the two implementations). We use SSE4.2 to
// ensure we can use the full neon2sse li... | 722 | 29.125 | 69 | h |
null | pytorch-main/caffe2/operators/quantized/int8_slice_op.h | #ifndef CAFFE2_OPERATORS_INT8_SLICE_OP_H_
#define CAFFE2_OPERATORS_INT8_SLICE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
#include "caffe2/operators/slice_op.h"
namespace caffe2 {
namespace int8 {
cl... | 3,024 | 31.180851 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_softmax_op.h | #ifndef CAFFE2_OPERATORS_INT8_SOFTMAX_OP_H_
#define CAFFE2_OPERATORS_INT8_SOFTMAX_OP_H_
#include <qnnpack.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
namespace caffe2 {
namespace int8 {
class Int8Softm... | 3,287 | 29.728972 | 80 | h |
null | pytorch-main/caffe2/operators/quantized/int8_test_utils.h | #ifndef CAFFE2_INT8_TEST_UTILS_H_
#define CAFFE2_INT8_TEST_UTILS_H_
#include "caffe2/core/common.h"
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/tensor_int8.h"
#include <array>
#include <cmath>
#include <random>
#include "gtest/gtest.h"
nam... | 3,880 | 31.341667 | 83 | h |
null | pytorch-main/caffe2/operators/quantized/int8_transpose_op.h | #ifndef CAFFE2_OPERATORS_INT8_TRANSPOSE_OP_H_
#define CAFFE2_OPERATORS_INT8_TRANSPOSE_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2/operators/quantized/int8_utils.h"
#include "caffe2/operators/transpose_op.h"
namespace caffe2 {
namespac... | 1,120 | 27.74359 | 73 | h |
null | pytorch-main/caffe2/operators/quantized/int8_utils.h | #ifndef CAFFE2_INT8_UTILS_H_
#define CAFFE2_INT8_UTILS_H_
#include <gemmlowp/public/gemmlowp.h>
#include "caffe2/utils/threadpool/ThreadPool.h"
#include "caffe2/utils/threadpool/WorkersPool.h"
namespace caffe2 {
/*
* Initialized QNNPACK (only once).
* Throws if initialization failed.
*/
void initQNNPACK();
name... | 4,737 | 28.987342 | 79 | h |
null | pytorch-main/caffe2/operators/rnn/recurrent_network_blob_fetcher_op.h | #ifndef CAFFE2_OPERATORS_RECURRENT_BLOB_FETCHER_OP_H_
#define CAFFE2_OPERATORS_RECURRENT_BLOB_FETCHER_OP_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/tensor.h"
#include "caffe2/operators/rnn/recurrent_network_op.h"
#include "google/protobu... | 2,289 | 31.253521 | 92 | h |
null | pytorch-main/caffe2/operators/rnn/recurrent_network_executor.h | #ifndef CAFFE2_OPERATORS_RECURRENT_NETWORK_EXECUTOR_H_
#define CAFFE2_OPERATORS_RECURRENT_NETWORK_EXECUTOR_H_
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/timer.h"
#include "caffe2/operators/rnn/recurrent_network_executor_incl.h"
#include "c1... | 17,661 | 32.199248 | 88 | h |
null | pytorch-main/caffe2/operators/rnn/recurrent_network_executor_gpu.h | #ifndef CAFFE2_OPERATORS_RECURRENT_NETWORK_GPU_EXECUTOR_H_
#define CAFFE2_OPERATORS_RECURRENT_NETWORK_GPU_EXECUTOR_H_
#include "caffe2/core/context_gpu.h"
#include "caffe2/operators/rnn/recurrent_network_executor.h"
#include <map>
namespace caffe2 {
class CUDARecurrentNetworkExecutor : public RecurrentNetworkExecu... | 2,434 | 28.337349 | 88 | h |
null | pytorch-main/caffe2/operators/rnn/recurrent_network_executor_incl.h |
#ifndef CAFFE2_OPERATORS_RECURRENT_NETWORK_EXECUTOR_INCL_H_
#define CAFFE2_OPERATORS_RECURRENT_NETWORK_EXECUTOR_INCL_H_
#include <vector>
#include "caffe2/core/operator.h"
namespace caffe2 {
/**
* Struct for operator in a timestep and its dependencies.
*/
struct RNNNetOperator {
int order; // Position in the st... | 2,202 | 27.986842 | 77 | h |
null | pytorch-main/caffe2/operators/rnn/recurrent_op_cudnn.h | #ifndef CAFFE2_OPERATORS_RECURRENT_OP_CUDNN_H_
#define CAFFE2_OPERATORS_RECURRENT_OP_CUDNN_H_
#include "caffe2/core/context.h"
#include "caffe2/core/context_gpu.h"
#include "caffe2/core/cudnn_wrappers.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
namespace detail {
template... | 4,233 | 27.039735 | 83 | h |
null | pytorch-main/caffe2/operators/rnn/hip/recurrent_op_miopen.h | #ifndef CAFFE2_OPERATORS_RECURRENT_OP_MIOPEN_H_
#define CAFFE2_OPERATORS_RECURRENT_OP_MIOPEN_H_
#include "caffe2/core/context.h"
#include "caffe2/core/hip/context_gpu.h"
#include "caffe2/core/hip/miopen_wrapper.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
namespace caffe2 {
namespace detail {... | 3,878 | 26.510638 | 79 | h |
null | pytorch-main/caffe2/opt/annotations.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/proto/caffe2_pb.h"
#include "nomnigraph/Representations/NeuralNet.h"
namespace caffe2 {
class TORCH_API Caffe2Annotation : public nom::repr::Annotation {
public:
Caffe2Annotation() : Annotation(AnnotationKind::Caffe2) {... | 2,141 | 30.043478 | 78 | h |
null | pytorch-main/caffe2/opt/backend_cutting.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/proto/caffe2_pb.h"
#include "nomnigraph/Representations/NeuralNet.h"
#include <functional>
namespace caffe2 {
namespace opt {
struct CutResult {
caffe2::NetDef net;
int numberOfSubnets{0};
};
TORCH_API void DumpGraph(nom::repr::NNGraph* g, const std:... | 586 | 23.458333 | 74 | h |
null | pytorch-main/caffe2/opt/backend_transformer_base.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/core/workspace.h"
#include "caffe2/opt/bound_shape_inferencer.h"
#include "caffe2/proto/caffe2_pb.h"
#include <string>
#include <unordered_map>
#include <vector>
namespace caffe2 {
namespace {
constexpr char kNetPos[] = "net_pos";
constexpr char kModelId[... | 2,773 | 26.74 | 79 | h |
null | pytorch-main/caffe2/opt/converter.h | #ifndef CAFFE2_OPT_CONVERTER_H
#define CAFFE2_OPT_CONVERTER_H
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/opt/annotations.h"
#include "caffe2/proto/caffe2_pb.h"
#include "nomnigraph/Graph/Graph.h"
#include "nomnigraph/Representations/ControlFlow.h"
#include "nomnigraph/Representat... | 3,014 | 37.164557 | 80 | h |
null | pytorch-main/caffe2/opt/distributed.h | #pragma once
#include "caffe2/core/common.h"
#include "caffe2/core/logging.h"
#include "caffe2/proto/caffe2_pb.h"
#include "nomnigraph/Representations/NeuralNet.h"
namespace caffe2 {
/// \brief Convert to an NNModule and apply a mapping of
/// tensor names to DeviceOptions to it.
///
/// This *only* applies the map ... | 1,126 | 32.147059 | 65 | h |
null | pytorch-main/caffe2/opt/fakefp16_transform.h | #pragma once
#include <string>
#include <unordered_map>
#include <vector>
#include <caffe2/core/net.h>
#include <caffe2/core/workspace.h>
#include <caffe2/proto/caffe2_pb.h>
namespace caffe2 {
namespace opt {
// Mapping from fp32 ops to fakefp16 ops
TORCH_API std::unordered_map<std::string, std::string> getFakeFp16... | 584 | 21.5 | 76 | h |
null | pytorch-main/caffe2/opt/fusion.h | /**
* 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 ... | 4,141 | 32.674797 | 79 | h |
null | pytorch-main/caffe2/opt/glow_net_transform.h | #pragma once
#include <string>
#include <unordered_set>
#include <vector>
#include <caffe2/core/net.h>
#include <caffe2/core/workspace.h>
#include <caffe2/opt/shape_info.h>
#include <caffe2/proto/caffe2_pb.h>
C10_DECLARE_string(onnxifi_blacklist);
C10_DECLARE_string(onnxifi_blacklist_ops);
namespace caffe2 {
namesp... | 1,625 | 34.347826 | 80 | h |
null | pytorch-main/caffe2/opt/onnxifi_op.h | #pragma once
#include <unordered_map>
#include "onnx/onnx_pb.h"
#include <c10/util/Exception.h>
#include <c10/util/SmallVector.h>
#include <c10/util/irange.h>
#include "caffe2/core/context.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/onnx/onnxifi_graph_info.h"
#include "caff... | 19,554 | 35.965974 | 119 | h |
null | pytorch-main/caffe2/opt/onnxifi_transformer.h | #pragma once
#include <cstdint>
#include <string>
#include <unordered_map>
#include <vector>
#include "caffe2/opt/backend_cutting.h"
#include "onnx/onnx_pb.h"
#include "caffe2/core/operator.h"
#include "caffe2/onnx/onnxifi_init.h"
#include "caffe2/opt/backend_transformer_base.h"
namespace caffe2 {
namespace onnx {
... | 6,859 | 31.511848 | 80 | h |
null | pytorch-main/caffe2/opt/passes.h | #ifndef CAFFE2_OPT_OPT_PASSS_H
#define CAFFE2_OPT_OPT_PASSS_H
#include "caffe2/core/common.h"
#include "caffe2/core/workspace.h"
#include "caffe2/proto/caffe2_pb.h"
#include "nomnigraph/Representations/NeuralNet.h"
using namespace nom::repr;
namespace caffe2 {
/* This file sets up the optimization pass registry.
... | 2,642 | 33.776316 | 91 | h |
null | pytorch-main/caffe2/opt/shape_info.h | #pragma once
#include "caffe2/core/operator.h"
namespace caffe2 {
struct TORCH_API QShapeInfo {
QShapeInfo(float o = 0, float s = 1, uint32_t a = 1) {
offset.clear();
scale.clear();
offset.push_back(o);
scale.push_back(s);
axis = a;
}
uint32_t axis;
vector<float> offset;
vector<float> ... | 4,784 | 27.825301 | 94 | h |
null | pytorch-main/caffe2/opt/tvm_transformer.h | #pragma once
#include "caffe2/opt/backend_transformer_base.h"
#include <unordered_set>
namespace caffe2 {
struct TvmTransformOptions final : public BackendTransformOptions {
explicit TvmTransformOptions() : BackendTransformOptions() {}
// Whether to enable profiling based jit
bool profiling_based_jit{false}... | 2,992 | 30.840426 | 79 | h |
null | pytorch-main/caffe2/opt/custom/cc_amrc.h | #pragma once
#include <immintrin.h>
#include "caffe2/core/context.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/types.h"
#include "caffe2/utils/math.h"
namespace caffe2 {
template <class Context>
class ConcatAddMulReplaceNaNClipOp final : public Operator<Context> {
public:
USE_OPERATOR_CONTEXT_FUNCTI... | 5,926 | 32.485876 | 84 | h |
null | pytorch-main/caffe2/opt/custom/freeze_quantization_params.h | #pragma once
#include <caffe2/core/workspace.h>
#include <caffe2/proto/caffe2_pb.h>
namespace caffe2 {
/// We have a variant of 2-input Int8Quantize and 4-input Int8FC where the last
/// input points to a blob which contains the y_scale and y_zero_point. It's
/// orginated from online snapshot update but is creating ... | 545 | 38 | 80 | h |
null | pytorch-main/caffe2/opt/nql/ast.h | #pragma once
#include "c10/util/irange.h"
#include <iostream>
#include <string>
#include <vector>
struct ASTExpr {
std::string name = "";
std::vector<ASTExpr*> children;
bool isCallFlag = false;
bool starInputsFlag = false;
~ASTExpr() {
for (ASTExpr* e : children)
delete e;
}
bool isCall() con... | 1,619 | 20.038961 | 67 | h |
null | pytorch-main/caffe2/opt/nql/graphmatcher.h | #include "ast.h"
#include "caffe2/opt/converter.h"
#include "nomnigraph/Transformations/SubgraphMatcher.h"
namespace nom {
namespace nql {
using Criteria = std::string;
using TestMatchGraph = nom::matcher::MatchGraph<nom::repr::NNGraph>;
using TestMatchPredicate = nom::matcher::MatchPredicate<nom::repr::NNGraph>;
/... | 4,659 | 34.037594 | 80 | h |
null | pytorch-main/caffe2/perfkernels/adagrad.h | #pragma once
#if defined(__AVX__) && !defined(__NVCC__) && \
(defined(__x86_64__) || defined(_M_X64) || defined(__i386__))
#define CAFFE2_PERFKERNELS_ADAGRAD_H_USE_INTRINSIC
#include <immintrin.h>
#endif
#include <c10/util/Half.h>
#include <c10/util/irange.h>
namespace caffe2 {
namespace internal {
// The follo... | 6,104 | 28.635922 | 80 | h |
null | pytorch-main/caffe2/perfkernels/batch_box_cox.h | // Impmenets BoxCox operator for CPU
#pragma once
#include <cstdint>
namespace caffe2 {
template <typename T>
void compute_batch_box_cox(
std::size_t N,
std::size_t D,
std::size_t block_size,
const T* self_data,
const T* lambda1_data,
const T* lambda2_data,
T* output_data);
extern templat... | 789 | 20.944444 | 51 | h |
null | pytorch-main/caffe2/perfkernels/common.h | // !!!! PLEASE READ !!!!
// Minimize (transitively) included headers from _avx*.cc because some of the
// functions defined in the headers compiled with platform dependent compiler
// options can be reused by other translation units generating illegal
// instruction run-time error.
// Common utilities for writing perf... | 5,526 | 41.515385 | 80 | h |
null | pytorch-main/caffe2/perfkernels/cvtsh_ss_bugfix.h | #pragma once
// Apple clang was fixed in 8.1
#if defined(__apple_build_version__) && \
((__clang_major__ < 8) || \
((__clang_major__ == 8) && (__clang_minor__ < 1)))
#define CAFFE2_INTERNAL_APPLE_NEED_FIX 1
#endif
// Regular clang was fixed in 3.9
#if defined(__clang__) && (__clang_major__ < 4) && ... | 2,062 | 26.144737 | 75 | h |
null | pytorch-main/caffe2/perfkernels/embedding_lookup.h | #pragma once
#include <cstdint>
namespace caffe2 {
/**
* Embedding lookup with reduction.
*
* `input` of size data_size * block_size
* `indices` of size index_size
* `lengths` of size output_size
* `weights` nullptr or array of size index_size
* `out` of size output_size * block_size
* sum(lengths[i]) == ind... | 1,539 | 27.518519 | 77 | h |
null | pytorch-main/caffe2/perfkernels/embedding_lookup_idx.h | #pragma once
#include <cstdint>
namespace caffe2 {
// clang-format off
/**
* Embedding lookup with reduction.
*
* `input` of size data_size * block_size
* `indices` of size index_size
* `offsets` of size output_size
* `weights` nullptr or array of size index_size
* `out` of size output_size * block_size
*
*... | 1,674 | 27.87931 | 85 | h |
null | pytorch-main/caffe2/perfkernels/fused_8bit_rowwise_embedding_lookup.h | #pragma once
#include <cstdint>
namespace caffe2 {
/**
* Embedding lookup with reduction.
*
* `input` of size data_size * (block_size + 8B)
* `indices` of size index_size
* `lengths` of size output_size
* `weights` nullptr or array of size index_size
* `out` of size output_size * block_size
* sum(lengths[i])... | 1,690 | 29.196429 | 79 | h |
null | pytorch-main/caffe2/perfkernels/fused_8bit_rowwise_embedding_lookup_idx.h | #pragma once
#include <cstdint>
namespace caffe2 {
/**
* Embedding lookup with reduction.
*
* `input` of size data_size * (block_size + 8B)
* `indices` of size index_size
* `offsets` of size output_size
* `weights` nullptr or array of size index_size
* `out` of size output_size * block_size
*
* Note that bl... | 1,807 | 30.172414 | 79 | h |
null | pytorch-main/caffe2/perfkernels/lstm_unit_cpu-impl.h | #pragma once
#include <string.h>
#include <cmath>
#include <cstdint>
#include "c10/util/irange.h"
#include "caffe2/utils/conversions.h"
#include "vectorizer.h"
namespace caffe2 {
namespace perfkernels {
namespace {
template <typename T>
inline T sigmoid(T x) {
return 1 / (1 + std::exp(-x));
}
template <typename T>... | 3,693 | 25.014085 | 72 | h |
null | pytorch-main/caffe2/perfkernels/math.h | #pragma once
#include <cstdint>
namespace caffe2 {
namespace math {
// Returns the quantized and compressed values of floating inputs
// The "fused" representation stores the [bitwidth][tail][min][max]
// with the quantized data in one array. Since we store 8/bitwidth
// quantized data in one byte, the last buckets... | 1,103 | 29.666667 | 70 | h |
null | pytorch-main/caffe2/perfkernels/vectorizer.h | #pragma once
#if (ENABLE_VECTORIZATION > 0) && !defined(_DEBUG) && !defined(DEBUG)
#if defined(__clang__) && (__clang_major__ > 7)
#define IS_SANITIZER \
((__has_feature(address_sanitizer) == 1) || \
(__has_feature(memory_sanitizer) == 1) || \
(__has_feature(thread_sanitizer) == 1) ||... | 810 | 26.965517 | 69 | h |
null | pytorch-main/caffe2/predictor/InferenceGraph.h | #pragma once
#include "caffe2/core/workspace.h"
namespace caffe2 {
/**
* This struct stores information about the inference graph which defines
* underlying math of BlackBoxPredictor. Other parts of it such as various
* threading optimizations don't belong here.
*/
struct InferenceGraph {
std::unique_ptr<NetDe... | 833 | 29.888889 | 80 | h |
null | pytorch-main/caffe2/predictor/ThreadLocalPtr.h | #pragma once
#include <mutex>
#include <unordered_map>
#include <unordered_set>
#include "caffe2/core/logging.h"
namespace caffe2 {
/**
* thread_local pointer in C++ is a per thread pointer. However, sometimes
* we want to have a thread local state that is per thread and also per
* instance. e.g. we have the foll... | 4,109 | 24.849057 | 80 | h |
null | pytorch-main/caffe2/predictor/predictor.h | #pragma once
#include <unordered_set>
#include "caffe2/core/net.h"
#include "caffe2/core/tensor.h"
#include "caffe2/predictor/predictor_config.h"
namespace caffe2 {
class TORCH_API Predictor {
public:
using TensorList = std::vector<TensorCPU>;
using TensorMap = std::unordered_map<std::string, TensorCPU>;
Pre... | 1,810 | 24.152778 | 77 | h |
null | pytorch-main/caffe2/predictor/predictor_config.h | #pragma once
#include <memory>
#include "caffe2/core/tensor.h"
#include "caffe2/core/workspace.h"
#include "caffe2/proto/metanet.pb.h"
#include "caffe2/proto/predictor_consts.pb.h"
namespace caffe2 {
/*
* Parameters for a Predictor provided by name.
* They are stored as shared_ptr to accommodate parameter sharing
... | 1,934 | 31.25 | 80 | h |
null | pytorch-main/caffe2/predictor/predictor_utils.h | #pragma once
#include "caffe2/core/db.h"
#include "caffe2/core/workspace.h"
#include "caffe2/predictor/predictor_config.h"
#include "caffe2/proto/metanet.pb.h"
namespace caffe2 {
namespace predictor_utils {
TORCH_API const NetDef& getNet(const MetaNetDef& def, const std::string& name);
const ::google::protobuf::Repe... | 802 | 27.678571 | 79 | h |
null | pytorch-main/caffe2/predictor/emulator/benchmark.h | #pragma once
#include "caffe2/core/logging.h"
#include "caffe2/predictor/emulator/emulator.h"
#include "caffe2/predictor/emulator/output_formatter.h"
#include "caffe2/predictor/emulator/profiler.h"
C10_DECLARE_int(warmup);
C10_DECLARE_int(iter);
C10_DECLARE_int(threads);
C10_DECLARE_int(runs);
C10_DECLARE_string(run_n... | 1,062 | 22.622222 | 55 | h |
null | pytorch-main/caffe2/predictor/emulator/data_filler.h | #pragma once
#include "caffe2/core/logging.h"
#include "caffe2/core/operator.h"
#include "caffe2/predictor/predictor.h"
#include "caffe2/utils/filler.h"
namespace caffe2 {
namespace emulator {
typedef caffe2::Predictor::TensorList TensorList_t;
/*
* A filler to initialize the parameters and inputs of a predictor
*... | 4,670 | 29.135484 | 78 | h |
null | pytorch-main/caffe2/predictor/emulator/net_supplier.h | #pragma once
#include <functional>
#include "caffe2/predictor/emulator/data_filler.h"
#include "caffe2/predictor/emulator/utils.h"
namespace caffe2 {
namespace emulator {
struct RunnableNet {
const caffe2::NetDef& netdef;
const Filler* filler;
std::string debug_info;
RunnableNet(
const caffe2::NetDef&... | 2,554 | 24.29703 | 73 | h |
null | pytorch-main/caffe2/predictor/emulator/std_output_formatter.h | #pragma once
#include "output_formatter.h"
namespace caffe2 {
namespace emulator {
const uint64_t MS_IN_SECOND = 1000;
/*
* Print the output of the emulator run to stdout.
*/
class StdOutputFormatter : public OutputFormatter {
private:
template <typename T>
static float get_mean(const std::vector<T>& values) ... | 1,365 | 28.695652 | 78 | h |
null | pytorch-main/caffe2/predictor/emulator/utils.h | #pragma once
#include <fstream>
#include "caffe2/core/logging.h"
namespace caffe2 {
namespace emulator {
/*
* Replace a @substring in a given @line with @target
*/
inline std::string replace(
std::string line,
const std::string& substring,
const std::string& target) {
size_t index = 0;
while (true)... | 1,584 | 22.308824 | 79 | h |
null | pytorch-main/caffe2/proto/caffe2_pb.h | #pragma once
#include <c10/core/Device.h>
#include <c10/util/Exception.h>
#include <caffe2/proto/caffe2.pb.h>
namespace caffe2 {
using DeviceType = at::DeviceType;
constexpr DeviceType CPU = DeviceType::CPU;
constexpr DeviceType CUDA = DeviceType::CUDA;
constexpr DeviceType OPENGL = DeviceType::OPENGL;
constexpr Devi... | 4,269 | 30.397059 | 83 | h |
null | pytorch-main/caffe2/python/dlpack.h | /*!
* Copyright (c) 2017 by Contributors
* \file dlpack.h
* \brief The common header of DLPack.
*/
#ifndef DLPACK_DLPACK_H_
#define DLPACK_DLPACK_H_
/**
* \brief Compatibility with C++
*/
#ifdef __cplusplus
#define DLPACK_EXTERN_C extern "C"
#else
#define DLPACK_EXTERN_C
#endif
/*! \brief The current version o... | 6,661 | 27.839827 | 80 | h |
null | pytorch-main/caffe2/python/pybind_state.h | #pragma once
#include <unordered_map>
#include "caffe2/core/context.h"
#include "caffe2/core/init.h"
#include "caffe2/core/logging.h"
#include "caffe2/core/memonger.h"
#include "caffe2/core/net.h"
#include "caffe2/core/operator.h"
#include "caffe2/core/scope_guard.h"
#include "caffe2/core/tensor.h"
#include "caffe2/c... | 15,149 | 31.371795 | 80 | h |
null | pytorch-main/caffe2/python/pybind_state_dlpack.h | #pragma once
#include "caffe2/core/context.h"
#include "caffe2/core/tensor.h"
#include "caffe2/core/types.h"
#include "caffe2/proto/caffe2_pb.h"
#include "caffe2/python/dlpack.h"
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
namespace caffe2 {
namespace python {
namespace py = pybind11;
const DLDeviceTy... | 4,152 | 29.536765 | 78 | h |
null | pytorch-main/caffe2/python/pybind_state_registry.h | #pragma once
#include <pybind11/pybind11.h>
#include "c10/util/Registry.h"
namespace caffe2 {
namespace python {
namespace py = pybind11;
struct PybindAddition {
PybindAddition() {}
PybindAddition(py::module&) {}
virtual ~PybindAddition(){};
};
C10_DECLARE_REGISTRY(PybindAdditionRegistry, PybindAddition, py:... | 1,021 | 31.967742 | 79 | h |
null | pytorch-main/caffe2/python/pybind_workspace.h | #pragma once
#include <pybind11/pybind11.h>
#include <pybind11/stl.h>
//#include <Python.h>
namespace caffe2 {
namespace python {
class C10_EXPORT BlobFetcherBase {
public:
struct FetchedBlob {
pybind11::object obj;
bool copied;
};
virtual ~BlobFetcherBase();
virtual pybind11::object Fetch(const Blo... | 1,206 | 27.069767 | 78 | h |
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