Reshape - 1 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Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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.
- Reshape1 → Reshape14 +15 -10
Reshape1 → Reshape14
RENAMED
@@ -1 +1 @@
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Reshape the input tensor similar to numpy.reshape.
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-
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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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-
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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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If the attribute 'allowzero' is set, it is invalid for the specified shape to
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contain both a zero value and -1, as the value of the dimension corresponding
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to -1 cannot be determined uniquely.
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### Attributes
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* **
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* **allowzero - INT** (default is '0'):
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(Optional) By default, when any value in the 'shape' input is equal to zero the corresponding dimension value is copied from the input tensor dynamically. allowzero=1 indicates that if any value in the 'shape' input is set to zero, the zero value is honored, similar to NumPy.
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legacy optimization attribute.
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-
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* **shape - INTS** :
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-
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New shape
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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 ( tensor(double), tensor(float), tensor(float16) ):
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* **T** in ( tensor(bfloat16), tensor(bool), tensor(complex128), tensor(complex64), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(string), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8) ):
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Constrain input and output types to
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Constrain input and output types to all tensor types.? ^ ^ +++++
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