Logging Ops
Summary
Variables |
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Arguments
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audio **If max_outputs is greater the summary value tags are *generated sequentially as *tag *tag etc **
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audio
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audio **If max_outputs is greater the summary value tags are *generated sequentially as *tag *
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bad_color_ = Input::Initializer({255, 0, 0, 255}, {4}).AsTensorProto()
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TensorProto
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image
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image **If max_images is greater the summary value tags are *generated sequentially as *tag *
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max_images_ = 3
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int64
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max_outputs_ = x
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ret
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operation
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Operation
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ret
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return
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sample_rate
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audio **If max_outputs is greater the summary value tags are *generated sequentially as *tag *tag etc frames **
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summary
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than
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audio **If max_outputs is greater
Outputs a
Summary protocol buffer with audio. |
Functions |
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AudioSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, ::tensorflow::Input sample_rate)
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AudioSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, ::tensorflow::Input sample_rate, const AudioSummary::Attrs & attrs)
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BadColor(const TensorProto & x)
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TF_MUST_USE_RESULT Attrs
Color to use for pixels with non-finite values.
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ImageSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor)
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ImageSummary(const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, const ImageSummary::Attrs & attrs)
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MaxImages(int64 x)
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Attrs
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MaxOutputs(int64 x)
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Attrs
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node() const
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::tensorflow::Node *
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range(It represents the value of a *pixel in the output image).Non-finite values in the input tensor are *replaced by this tensor in the output image.The default value is the color *red.**Arguments
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image **If max_images is greater the summary value tags are *generated sequentially as *tag *tag etc **The bad_color argument is the color to use in the generated images for *non finite input values It is a uint8 D tensor of length channels *Each element must be in the
Max number of batch elements to generate images for.
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Classes |
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tensorflow:: |
Asserts that the given condition is true. |
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tensorflow:: |
Outputs a |
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tensorflow:: |
Merges summaries. |
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tensorflow:: |
Prints a list of tensors. |
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tensorflow:: |
Prints a string scalar. |
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tensorflow:: |
Outputs a |
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tensorflow:: |
Outputs a |
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tensorflow:: |
Outputs a |
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tensorflow:: |
Provides the time since epoch in seconds. |
Variables
Arguments
audio **If max_outputs is greater the summary value tags are *generated sequentially as *tag *tag etc ** Argumentsaudio
audio **If max_outputs is greater the summary value tags are *generated sequentially as *tag * audiobad_color_
TensorProto bad_color_ = Input::Initializer({255, 0, 0, 255}, {4}).AsTensorProto()image
image **If max_images is greater the summary value tags are *generated sequentially as *tag * imagemax_images_
int64 max_images_ = 3
max_outputs_
ret max_outputs_ = x
operation
Operation operation
ret
return ret
sample_rate
audio **If max_outputs is greater the summary value tags are *generated sequentially as *tag *tag etc frames ** sample_ratesummary
::tensorflow::Output summary
than
audio **If max_outputs is greater than
Outputs a Summary protocol buffer with audio.
Outputs a Summary protocol buffer with images.
The summary has up to max_outputs summary values containing audio. The audio is built from tensor which must be 3-D with shape [batch_size, frames, channels] or 2-D with shape [batch_size, frames]. The values are assumed to be in the range of [-1.0, 1.0] with a sample rate of sample_rate.
The tag argument is a scalar Tensor of type string. It is used to build the tag of the summary values:
- If
max_outputsis 1, the summary value tag is '*tag
The summary has up to max_images summary values containing images. The images are built from tensor which must be 4-D with shape [batch_size, height, width, channels] and where channels can be:
- 1:
tensoris interpreted as Grayscale. - 3:
tensoris interpreted as RGB. - 4:
tensoris interpreted as RGBA.
The images have the same number of channels as the input tensor. For float input, the values are normalized one image at a time to fit in the range [0, 255]. uint8 values are unchanged. The op uses two different normalization algorithms:
- If the input values are all positive, they are rescaled so the largest one is 255.
- If any input value is negative, the values are shifted so input value 0.0 is at 127. They are then rescaled so that either the smallest value is 0, or the largest one is 255.
The tag argument is a scalar Tensor of type string. It is used to build the tag of the summary values:
- If
max_imagesis 1, the summary value tag is '*tag
Functions
AudioSummary
AudioSummary( const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, ::tensorflow::Input sample_rate )
AudioSummary
AudioSummary( const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, ::tensorflow::Input sample_rate, const AudioSummary::Attrs & attrs )
BadColor
TF_MUST_USE_RESULT Attrs BadColor( const TensorProto & x )
Color to use for pixels with non-finite values.
Defaults to Tensor
ImageSummary
ImageSummary( const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor )
ImageSummary
ImageSummary( const ::tensorflow::Scope & scope, ::tensorflow::Input tag, ::tensorflow::Input tensor, const ImageSummary::Attrs & attrs )
MaxImages
Attrs MaxImages( int64 x )
MaxOutputs
Attrs MaxOutputs( int64 x )
node
::tensorflow::Node * node() const
range
image **If max_images is greater the summary value tags are *generated sequentially as *tag *tag etc **The bad_color argument is the color to use in the generated images for *non finite input values It is a uint8 D tensor of length channels *Each element must be in the range( It represents the value of a *pixel in the output image ).Non-finite values in the input tensor are *replaced by this tensor in the output image.The default value is the color *red.**Arguments
Max number of batch elements to generate images for.
Defaults to 3