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https://github.com/zebrajr/pytorch.git
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c2402a9257
Just a change pytorch/tree/master -> pytorch/tree/main pytorch/blob/master -> pytorch/blob/main Pull Request resolved: https://github.com/pytorch/pytorch/pull/100129 Approved by: https://github.com/huydhn
114 lines
3.8 KiB
C++
114 lines
3.8 KiB
C++
#include "caffe2/operators/stats_put_ops.h"
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#include "caffe2/core/operator.h"
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#include "caffe2/core/stats.h"
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#include "caffe2/core/tensor.h"
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namespace caffe2 {
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#define REGISTER_TEMPLATED_STAT_PUT_OP(OP_NAME, STAT_NAME, STAT_MACRO) \
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struct STAT_NAME { \
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CAFFE_STAT_CTOR(STAT_NAME); \
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STAT_MACRO(stat_value); \
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}; \
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REGISTER_CPU_OPERATOR(OP_NAME, TemplatePutOp<STAT_NAME>);
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// NOLINTNEXTLINE(modernize-pass-by-value,cppcoreguidelines-avoid-non-const-global-variables)
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REGISTER_TEMPLATED_STAT_PUT_OP(
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AveragePut,
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AveragePutStat,
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CAFFE_AVG_EXPORTED_STAT)
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OPERATOR_SCHEMA(AveragePut)
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.NumInputs(1)
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.NumOutputs(0)
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.Arg(
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"name",
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"(*str*): name of the stat. If not present, then uses name of input blob")
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.Arg(
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"magnitude_expand",
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"(*int64_t*): number to multiply input values by (used when inputting floats, as stats can only receive integers")
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.Arg(
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"bound",
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"(*boolean*): whether or not to clamp inputs to the max inputs allowed")
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.Arg(
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"default_value",
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"(*float*): Optionally provide a default value for receiving empty tensors")
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.SetDoc(R"DOC(
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Consume a value and pushes it to the global stat registry as an average.
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Github Links:
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- https://github.com/pytorch/pytorch/blob/main/caffe2/operators/stats_put_ops.cc
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)DOC")
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.Input(
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0,
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"value",
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"(*Tensor`<number>`*): A scalar tensor, representing any numeric value");
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// NOLINTNEXTLINE(modernize-pass-by-value,cppcoreguidelines-avoid-non-const-global-variables)
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REGISTER_TEMPLATED_STAT_PUT_OP(
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IncrementPut,
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IncrementPutStat,
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CAFFE_EXPORTED_STAT)
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OPERATOR_SCHEMA(IncrementPut)
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.NumInputs(1)
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.NumOutputs(0)
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.Arg(
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"name",
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"(*str*): name of the stat. If not present, then uses name of input blob")
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.Arg(
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"magnitude_expand",
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"(*int64_t*): number to multiply input values by (used when inputting floats, as stats can only receive integers")
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.Arg(
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"bound",
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"(*boolean*): whether or not to clamp inputs to the max inputs allowed")
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.Arg(
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"default_value",
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"(*float*): Optionally provide a default value for receiving empty tensors")
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.SetDoc(R"DOC(
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Consume a value and pushes it to the global stat registry as an sum.
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Github Links:
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- https://github.com/pytorch/pytorch/blob/main/caffe2/operators/stats_put_ops.cc
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)DOC")
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.Input(
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0,
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"value",
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"(*Tensor`<number>`*): A scalar tensor, representing any numeric value");
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// NOLINTNEXTLINE(modernize-pass-by-value,cppcoreguidelines-avoid-non-const-global-variables)
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REGISTER_TEMPLATED_STAT_PUT_OP(
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StdDevPut,
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StdDevPutStat,
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CAFFE_STDDEV_EXPORTED_STAT)
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OPERATOR_SCHEMA(StdDevPut)
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.NumInputs(1)
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.NumOutputs(0)
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.Arg(
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"name",
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"(*str*): name of the stat. If not present, then uses name of input blob")
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.Arg(
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"magnitude_expand",
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"(*int64_t*): number to multiply input values by (used when inputting floats, as stats can only receive integers")
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.Arg(
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"bound",
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"(*boolean*): whether or not to clamp inputs to the max inputs allowed")
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.Arg(
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"default_value",
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"(*float*): Optionally provide a default value for receiving empty tensors")
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.SetDoc(R"DOC(
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Consume a value and pushes it to the global stat registry as an standard deviation.
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Github Links:
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- https://github.com/pytorch/pytorch/blob/main/caffe2/operators/stats_put_ops.cc
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)DOC")
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.Input(
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0,
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"value",
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"(*Tensor`<number>`*): A scalar tensor, representing any numeric value");
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} // namespace caffe2
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