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		Accelerator
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		Constant
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		Generator
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		Full Train Step
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		Eval Step
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		Train Step
Flatten
Description
Flattens the input tensor into a 2D matrix. If input tensor has shape (d_0, d_1, β¦ d_n) then the output will have shape (d_0 X d_1 β¦ d_(axis-1), d_axis X d_(axis+1) β¦ X dn).

Input parameters
 specified_outputs_name :Β array, this parameter lets you manually assign custom names to the output tensors of a node.
 specified_outputs_name :Β array, this parameter lets you manually assign custom names to the output tensors of a node.
 Β input (heterogeneous) – T : object, aΒ tensor of rank >= axis.
Β input (heterogeneous) – T : object, aΒ tensor of rank >= axis.
 Β Parameters :Β cluster,
Β Parameters :Β cluster,
 axis : integer, indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 β¦ d_n), where the shape of the input tensor is (d_0, d_1, β¦ d_n).
 axis : integer, indicate up to which input dimensions (exclusive) should be flattened to the outer dimension of the output. The value for axis must be in the range [-r, r], where r is the rank of the input tensor. Negative value means counting dimensions from the back. When axis = 0, the shape of the output tensor is (1, (d_0 X d_1 β¦ d_n), where the shape of the input tensor is (d_0, d_1, β¦ d_n).
Default value β1β.
 Β training?Β :Β boolean, whether the layer is in training mode (can store data for backward).
Β training?Β :Β boolean, whether the layer is in training mode (can store data for backward).
Default value βTrueβ.
 Β lda coeff :Β float, defines the coefficient by which the loss derivative will be multiplied before being sent to the previous layer (since during the backward run we go backwards).
Β lda coeff :Β float, defines the coefficient by which the loss derivative will be multiplied before being sent to the previous layer (since during the backward run we go backwards).
Default value β1β.
 Β name (optional) :Β string, name of the node.
Β name (optional) :Β string, name of the node.
 
			Output parameters
 Β output (heterogeneous) – T : object, aΒ 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the output.
Β output (heterogeneous) – T : object, aΒ 2D tensor with the contents of the input tensor, with input dimensions up to axis flattened to the outer dimension of the output and remaining input dimensions flattened into the inner dimension of the output.
Type Constraints
tensor(bfloat16),Β tensor(bool),Β tensor(complex128),Β tensor(complex64),Β tensor(double),Β tensor(float),Β tensor(float16),tensor(int16),Β tensor(int32),Β tensor(int64),Β tensor(int8),Β tensor(string),Β tensor(uint16),Β tensor(uint32),Β tensor(uint64),Β tensor(uint8)) : Constrain input and output to all tensor types.