tensorflow/core/ops/debug_ops.cc - platform/external/tensorflow - Git at Google

 /* Copyright 2017 The TensorFlow Authors. All Rights Reserved.

 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 to in writing, software
 distributed under the License is distributed on an "AS IS" BASIS,
 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 // This file registers all TensorFlow Debugger (tfdbg) ops.

 #include "tensorflow/core/framework/common_shape_fns.h"
 #include "tensorflow/core/framework/op.h"
 #include "tensorflow/core/framework/shape_inference.h"

 namespace tensorflow {

 // TensorFlow Debugger-inserted ops.
 // These ops are used only internally by tfdbg. There is no API for users to
 // direct create them. Users can create them indirectly by using
 // RunOptions.debug_options during Session::Run() call. See tfdbg documentation
 // for more details.
 REGISTER_OP("Copy")
     .Input("input: T")
     .Output("output: T")
     .Attr("T: type")
     .Attr("tensor_name: string = ''")
     .Attr("debug_ops_spec: list(string) = []")
     .SetAllowsUninitializedInput()
     .SetShapeFn(shape_inference::UnchangedShape)
     .Doc(R"doc(
 Copy Op.

 Performs CPU-to-CPU or GPU-to-GPU deep-copying of tensor, depending on the
 device on which the tensor is allocated.
 N.B.: If the all downstream attached debug ops are disabled given the current
 gRPC gating status, the output will simply forward the input tensor without
 deep-copying. See the documentation of Debug* ops for more details.

 Unlike the CopyHost Op, this op does not have HostMemory constraint on its
 input or output.

 input: Input tensor.
 output: Output tensor, deep-copied from input.
 tensor_name: The name of the input tensor.
 debug_ops_spec: A list of debug op spec (op, url, gated_grpc) for attached debug
   ops. Each element of the list has the format
   <debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented
   as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1",
   "DebugIdentity;file:///tmp/tfdbg_1;0".
 )doc");

 REGISTER_OP("CopyHost")
     .Input("input: T")
     .Output("output: T")
     .Attr("T: type")
     .Attr("tensor_name: string = ''")
     .Attr("debug_ops_spec: list(string) = []")
     .SetAllowsUninitializedInput()
     .SetShapeFn(shape_inference::UnchangedShape)
     .Doc(R"doc(
 Copy Host Op.

 Performs CPU-to-CPU deep-copying of tensor.
 N.B.: If the all downstream attached debug ops are disabled given the current
 gRPC gating status, the output will simply forward the input tensor without
 deep-copying. See the documentation of Debug* ops for more details.

 Unlike the Copy Op, this op has HostMemory constraint on its input or output.

 input: Input tensor.
 output: Output tensor, deep-copied from input.
 tensor_name: The name of the input tensor.
 debug_ops_spec: A list of debug op spec (op, url, gated_grpc) for attached debug
   ops. Each element of the list has the format
   <debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented
   as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1",
   "DebugIdentity;file:///tmp/tfdbg_1;0".
 )doc");

 REGISTER_OP("DebugIdentity")
     .Input("input: T")
     .Output("output: T")
     .Attr("T: type")
     .Attr("device_name: string = ''")
     .Attr("tensor_name: string = ''")
     .Attr("debug_urls: list(string) = []")
     .Attr("gated_grpc: bool = false")
     .SetAllowsUninitializedInput()
     .SetShapeFn(shape_inference::UnchangedShape)
     .Doc(R"doc(
 Debug Identity Op.

 Provides an identity mapping of the non-Ref type input tensor for debugging.

 input: Input tensor, non-Reference type.
 output: Output tensor that equals the input tensor.
 tensor_name: Name of the input tensor.
 debug_urls: List of URLs to debug targets, e.g.,
   file:///foo/tfdbg_dump, grpc:://localhost:11011
 gated_grpc: Whether this op will be gated. If any of the debug_urls of this
   debug node is of the grpc:// scheme, when the value of this attribute is set
   to True, the data will not actually be sent via the grpc stream unless this
   debug op has been enabled at the debug_url. If all of the debug_urls of this
   debug node are of the grpc:// scheme and the debug op is enabled at none of
   them, the output will be an empty Tensor.
 )doc");

 REGISTER_OP("DebugNanCount")
     .Input("input: T")
     .Output("output: int64")  // The debug signal (nan count) is int64
     .Attr("T: type")
     .Attr("device_name: string = ''")
     .Attr("tensor_name: string = ''")
     .Attr("debug_urls: list(string) = []")
     .Attr("gated_grpc: bool = false")
     .SetAllowsUninitializedInput()
     .SetShapeFn(shape_inference::ScalarShape)
     .Doc(R"doc(
 Debug NaN Value Counter Op

 Counts number of NaNs in the input tensor, for debugging.

 input: Input tensor, non-Reference type.
 output: An integer output tensor that is the number of NaNs in the input.
 tensor_name: Name of the input tensor.
 debug_urls: List of URLs to debug targets, e.g.,
   file:///foo/tfdbg_dump, grpc:://localhost:11011.
 gated_grpc: Whether this op will be gated. If any of the debug_urls of this
   debug node is of the grpc:// scheme, when the value of this attribute is set
   to True, the data will not actually be sent via the grpc stream unless this
   debug op has been enabled at the debug_url. If all of the debug_urls of this
   debug node are of the grpc:// scheme and the debug op is enabled at none of
   them, the output will be an empty Tensor.
 )doc");

 REGISTER_OP("DebugNumericSummary")
     .Input("input: T")
     .Output("output: double")
     .Attr("T: type")
     .Attr("device_name: string = ''")
     .Attr("tensor_name: string = ''")
     .Attr("debug_urls: list(string) = []")
     .Attr("lower_bound: float = -inf")
     .Attr("upper_bound: float = inf")
     .Attr("mute_if_healthy: bool = false")
     .Attr("gated_grpc: bool = false")
     .SetAllowsUninitializedInput()
     // Note: this could return a more specific shape if needed in future.
     .SetShapeFn(shape_inference::UnknownShape)
     .Doc(R"doc(
 Debug Numeric Summary Op.

 Provide a basic summary of numeric value types, range and distribution.

 input: Input tensor, non-Reference type, float or double.
 output: A double tensor of shape [14 + nDimensions], where nDimensions is the
   the number of dimensions of the tensor's shape. The elements of output are:
   [0]: is initialized (1.0) or not (0.0).
   [1]: total number of elements
   [2]: NaN element count
   [3]: generalized -inf count: elements <= lower_bound. lower_bound is -inf by
     default.
   [4]: negative element count (excluding -inf), if lower_bound is the default
     -inf. Otherwise, this is the count of elements > lower_bound and < 0.
   [5]: zero element count
   [6]: positive element count (excluding +inf), if upper_bound is the default
     -inf. Otherwise, this is the count of elements < upper_bound and > 0.
   [7]: generalized +inf count, elements >= upper_bound. upper_bound is +inf by
     default.
 Output elements [1:8] are all zero, if the tensor is uninitialized.
   [8]: minimum of all non-inf and non-NaN elements.
        If uninitialized or no such element exists: +inf.
   [9]: maximum of all non-inf and non-NaN elements.
        If uninitialized or no such element exists: -inf.
   [10]: mean of all non-inf and non-NaN elements.
         If uninitialized or no such element exists: NaN.
   [11]: variance of all non-inf and non-NaN elements.
         If uninitialized or no such element exists: NaN.
   [12]: Data type of the tensor encoded as an enum integer. See the DataType
         proto for more details.
   [13]: Number of dimensions of the tensor (ndims).
   [14+]: Sizes of the dimensions.

 tensor_name: Name of the input tensor.
 debug_urls: List of URLs to debug targets, e.g.,
   file:///foo/tfdbg_dump, grpc:://localhost:11011
 lower_bound: (float) The lower bound <= which values will be included in the
   generalized -inf count. Default: -inf.
 upper_bound: (float) The upper bound >= which values will be included in the
   generalized +inf count. Default: +inf.
 mute_if_healthy: (bool) Do not send data to the debug URLs unless at least one
   of elements [2], [3] and [7] (i.e., the nan count and the generalized -inf and
   inf counts) is non-zero.
 gated_grpc: Whether this op will be gated. If any of the debug_urls of this
   debug node is of the grpc:// scheme, when the value of this attribute is set
   to True, the data will not actually be sent via the grpc stream unless this
   debug op has been enabled at the debug_url. If all of the debug_urls of this
   debug node are of the grpc:// scheme and the debug op is enabled at none of
   them, the output will be an empty Tensor.

 )doc");

 }  // namespace tensorflow
	/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.

	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 to in writing, software
	distributed under the License is distributed on an "AS IS" BASIS,
	WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	See the License for the specific language governing permissions and
	limitations under the License.
	==============================================================================*/
	// This file registers all TensorFlow Debugger (tfdbg) ops.

	#include "tensorflow/core/framework/common_shape_fns.h"
	#include "tensorflow/core/framework/op.h"
	#include "tensorflow/core/framework/shape_inference.h"

	namespace tensorflow {

	// TensorFlow Debugger-inserted ops.
	// These ops are used only internally by tfdbg. There is no API for users to
	// direct create them. Users can create them indirectly by using
	// RunOptions.debug_options during Session::Run() call. See tfdbg documentation
	// for more details.
	REGISTER_OP("Copy")
	.Input("input: T")
	.Output("output: T")
	.Attr("T: type")
	.Attr("tensor_name: string = ''")
	.Attr("debug_ops_spec: list(string) = []")
	.SetAllowsUninitializedInput()
	.SetShapeFn(shape_inference::UnchangedShape)
	.Doc(R"doc(
	Copy Op.

	Performs CPU-to-CPU or GPU-to-GPU deep-copying of tensor, depending on the
	device on which the tensor is allocated.
	N.B.: If the all downstream attached debug ops are disabled given the current
	gRPC gating status, the output will simply forward the input tensor without
	deep-copying. See the documentation of Debug* ops for more details.

	Unlike the CopyHost Op, this op does not have HostMemory constraint on its
	input or output.

	input: Input tensor.
	output: Output tensor, deep-copied from input.
	tensor_name: The name of the input tensor.
	debug_ops_spec: A list of debug op spec (op, url, gated_grpc) for attached debug
	ops. Each element of the list has the format
	<debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented
	as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1",
	"DebugIdentity;file:///tmp/tfdbg_1;0".
	)doc");

	REGISTER_OP("CopyHost")
	.Input("input: T")
	.Output("output: T")
	.Attr("T: type")
	.Attr("tensor_name: string = ''")
	.Attr("debug_ops_spec: list(string) = []")
	.SetAllowsUninitializedInput()
	.SetShapeFn(shape_inference::UnchangedShape)
	.Doc(R"doc(
	Copy Host Op.

	Performs CPU-to-CPU deep-copying of tensor.
	N.B.: If the all downstream attached debug ops are disabled given the current
	gRPC gating status, the output will simply forward the input tensor without
	deep-copying. See the documentation of Debug* ops for more details.

	Unlike the Copy Op, this op has HostMemory constraint on its input or output.

	input: Input tensor.
	output: Output tensor, deep-copied from input.
	tensor_name: The name of the input tensor.
	debug_ops_spec: A list of debug op spec (op, url, gated_grpc) for attached debug
	ops. Each element of the list has the format
	<debug_op>;<grpc_url>;<gated_grpc>, wherein gated_grpc is boolean represented
	as 0/1. E.g., "DebugIdentity;grpc://foo:3333;1",
	"DebugIdentity;file:///tmp/tfdbg_1;0".
	)doc");

	REGISTER_OP("DebugIdentity")
	.Input("input: T")
	.Output("output: T")
	.Attr("T: type")
	.Attr("device_name: string = ''")
	.Attr("tensor_name: string = ''")
	.Attr("debug_urls: list(string) = []")
	.Attr("gated_grpc: bool = false")
	.SetAllowsUninitializedInput()
	.SetShapeFn(shape_inference::UnchangedShape)
	.Doc(R"doc(
	Debug Identity Op.

	Provides an identity mapping of the non-Ref type input tensor for debugging.

	input: Input tensor, non-Reference type.
	output: Output tensor that equals the input tensor.
	tensor_name: Name of the input tensor.
	debug_urls: List of URLs to debug targets, e.g.,
	file:///foo/tfdbg_dump, grpc:://localhost:11011
	gated_grpc: Whether this op will be gated. If any of the debug_urls of this
	debug node is of the grpc:// scheme, when the value of this attribute is set
	to True, the data will not actually be sent via the grpc stream unless this
	debug op has been enabled at the debug_url. If all of the debug_urls of this
	debug node are of the grpc:// scheme and the debug op is enabled at none of
	them, the output will be an empty Tensor.
	)doc");

	REGISTER_OP("DebugNanCount")
	.Input("input: T")
	.Output("output: int64") // The debug signal (nan count) is int64
	.Attr("T: type")
	.Attr("device_name: string = ''")
	.Attr("tensor_name: string = ''")
	.Attr("debug_urls: list(string) = []")
	.Attr("gated_grpc: bool = false")
	.SetAllowsUninitializedInput()
	.SetShapeFn(shape_inference::ScalarShape)
	.Doc(R"doc(
	Debug NaN Value Counter Op

	Counts number of NaNs in the input tensor, for debugging.

	input: Input tensor, non-Reference type.
	output: An integer output tensor that is the number of NaNs in the input.
	tensor_name: Name of the input tensor.
	debug_urls: List of URLs to debug targets, e.g.,
	file:///foo/tfdbg_dump, grpc:://localhost:11011.
	gated_grpc: Whether this op will be gated. If any of the debug_urls of this
	debug node is of the grpc:// scheme, when the value of this attribute is set
	to True, the data will not actually be sent via the grpc stream unless this
	debug op has been enabled at the debug_url. If all of the debug_urls of this
	debug node are of the grpc:// scheme and the debug op is enabled at none of
	them, the output will be an empty Tensor.
	)doc");

	REGISTER_OP("DebugNumericSummary")
	.Input("input: T")
	.Output("output: double")
	.Attr("T: type")
	.Attr("device_name: string = ''")
	.Attr("tensor_name: string = ''")
	.Attr("debug_urls: list(string) = []")
	.Attr("lower_bound: float = -inf")
	.Attr("upper_bound: float = inf")
	.Attr("mute_if_healthy: bool = false")
	.Attr("gated_grpc: bool = false")
	.SetAllowsUninitializedInput()
	// Note: this could return a more specific shape if needed in future.
	.SetShapeFn(shape_inference::UnknownShape)
	.Doc(R"doc(
	Debug Numeric Summary Op.

	Provide a basic summary of numeric value types, range and distribution.

	input: Input tensor, non-Reference type, float or double.
	output: A double tensor of shape [14 + nDimensions], where nDimensions is the
	the number of dimensions of the tensor's shape. The elements of output are:
	[0]: is initialized (1.0) or not (0.0).
	[1]: total number of elements
	[2]: NaN element count
	[3]: generalized -inf count: elements <= lower_bound. lower_bound is -inf by
	default.
	[4]: negative element count (excluding -inf), if lower_bound is the default
	-inf. Otherwise, this is the count of elements > lower_bound and < 0.
	[5]: zero element count
	[6]: positive element count (excluding +inf), if upper_bound is the default
	-inf. Otherwise, this is the count of elements < upper_bound and > 0.
	[7]: generalized +inf count, elements >= upper_bound. upper_bound is +inf by
	default.
	Output elements [1:8] are all zero, if the tensor is uninitialized.
	[8]: minimum of all non-inf and non-NaN elements.
	If uninitialized or no such element exists: +inf.
	[9]: maximum of all non-inf and non-NaN elements.
	If uninitialized or no such element exists: -inf.
	[10]: mean of all non-inf and non-NaN elements.
	If uninitialized or no such element exists: NaN.
	[11]: variance of all non-inf and non-NaN elements.
	If uninitialized or no such element exists: NaN.
	[12]: Data type of the tensor encoded as an enum integer. See the DataType
	proto for more details.
	[13]: Number of dimensions of the tensor (ndims).
	[14+]: Sizes of the dimensions.

	tensor_name: Name of the input tensor.
	debug_urls: List of URLs to debug targets, e.g.,
	file:///foo/tfdbg_dump, grpc:://localhost:11011
	lower_bound: (float) The lower bound <= which values will be included in the
	generalized -inf count. Default: -inf.
	upper_bound: (float) The upper bound >= which values will be included in the
	generalized +inf count. Default: +inf.
	mute_if_healthy: (bool) Do not send data to the debug URLs unless at least one
	of elements [2], [3] and [7] (i.e., the nan count and the generalized -inf and
	inf counts) is non-zero.
	gated_grpc: Whether this op will be gated. If any of the debug_urls of this
	debug node is of the grpc:// scheme, when the value of this attribute is set
	to True, the data will not actually be sent via the grpc stream unless this
	debug op has been enabled at the debug_url. If all of the debug_urls of this
	debug node are of the grpc:// scheme and the debug op is enabled at none of
	them, the output will be an empty Tensor.

	)doc");

	} // namespace tensorflow