Reshape - 13 vs 14#

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text. Green means an addition to the newer version, red means a deletion. Anything else is unchanged.

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  1. Reshape13 → Reshape14 +1 -12
Reshape13 → Reshape14 RENAMED
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  Reshape the input tensor similar to numpy.reshape.
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  First input is the data tensor, second input is a shape tensor which specifies the output shape. It outputs the reshaped tensor.
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  At most one dimension of the new shape can be -1. In this case, the value is
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  inferred from the size of the tensor and the remaining dimensions. A dimension
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  could also be 0, in which case the actual dimension value is unchanged (i.e. taken
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- from the input tensor). If 'allowzero' is set, and the new shape includes 0, the
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- dimension will be set explicitly to zero (i.e. not taken from input tensor).
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- Shape (second input) could be an empty shape, which means converting to a scalar.
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+ from the input tensor). Shape (second input) could be an empty shape, which means converting to a scalar.
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  The input tensor's shape and the output tensor's shape are required to have the same number of elements.
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-
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- **Attributes**
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-
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- * **allowzero**:
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- (Optional) By default, when any value in the 'shape' input is equal
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- to zero the corresponding dimension value is copied from the input
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- tensor dynamically. allowzero=1 indicates that if any value in the
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- 'shape' input is set to zero, the zero value is honored, similar to
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- NumPy.
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  **Inputs**
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  * **data** (heterogeneous) - **T**:
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  An input tensor.
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  * **shape** (heterogeneous) - **tensor(int64)**:
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  Specified shape for output.
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  **Outputs**
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  * **reshaped** (heterogeneous) - **T**:
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  Reshaped data.
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  **Type Constraints**
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  * **T** in (
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  tensor(bfloat16),
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  tensor(bool),
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  tensor(complex128),
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  tensor(complex64),
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  tensor(double),
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  tensor(float),
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  tensor(float16),
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  tensor(int16),
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  tensor(int32),
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  tensor(int64),
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  tensor(int8),
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  tensor(string),
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  tensor(uint16),
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  tensor(uint32),
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  tensor(uint64),
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  tensor(uint8)
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  ):
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  Constrain input and output types to all tensor types.