Cast - 9 vs 13#

Next section compares an older to a newer version of the same operator after both definition are converted into markdown text.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. Cast9 → Cast13 +0 -18
Cast9 → Cast13 RENAMED
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  The operator casts the elements of a given input tensor to a data type
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  specified by the 'to' argument and returns an output tensor of the same size in
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  the converted type. The 'to' argument must be one of the data types specified
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  in the 'DataType' enum field in the TensorProto message.
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  Casting from string tensor in plain (e.g., "3.14" and "1000") and scientific numeric representations
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  (e.g., "1e-5" and "1E8") to float types is supported. For example, converting string "100.5" to an integer may
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  result 100. There are some string literals reserved for special floating-point values;
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  "+INF" (and "INF"), "-INF", and "NaN" are positive infinity, negative infinity, and not-a-number, respectively.
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  Any string which can exactly match "+INF" in a case-insensitive way would be mapped to positive infinite. Similarly,
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  this case-insensitive rule is applied to "INF" and "NaN". When casting from numeric tensors
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  to string tensors, plain floating-point representation (such as "314.15926") would be used.
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  Converting non-numerical-literal string such as "Hello World!" is an undefined behavior. Cases
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  of converting string representing floating-point arithmetic value, such as "2.718", to INT is an undefined behavior.
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  Conversion from a numerical type to any numerical type is always allowed.
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  User must be aware of precision loss and value change caused by range difference between two types.
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  For example, a 64-bit float 3.1415926459 may be round to a 32-bit float 3.141592. Similarly, converting
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  an integer 36 to Boolean may produce 1 because we truncate bits which can't be stored in the targeted type.
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-
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- In more detail, the conversion among numerical types should follow these rules:
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-
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- * Casting from floating point to:
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- * floating point: +/- infinity if OOR (out of range).
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- * fixed point: undefined if OOR.
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- * bool: +/- 0.0 to False; all else to True.
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- * Casting from fixed point to:
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- * floating point: +/- infinity if OOR. (+ infinity in the case of uint)
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- * fixed point: when OOR, discard higher bits and reinterpret (with respect to two's complement representation for
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- signed types). For example, 200 (int16) -> -56 (int8).
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- * bool: zero to False; nonzero to True.
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- * Casting from bool to:
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- * floating point: {1.0, 0.0}.
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- * fixed point: {1, 0}.
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- * bool: no change.
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  **Attributes**
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  * **to** (required):
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  The data type to which the elements of the input tensor are cast.
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  Strictly must be one of the types from DataType enum in TensorProto
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  **Inputs**
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  * **input** (heterogeneous) - **T1**:
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  Input tensor to be cast.
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  **Outputs**
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  * **output** (heterogeneous) - **T2**:
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  Output tensor with the same shape as input with type specified by
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  the 'to' argument
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  **Type Constraints**
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  * **T1** in (
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- tensor(bfloat16),
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  tensor(bool),
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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 types. Casting from complex is not supported.
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  * **T2** in (
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- tensor(bfloat16),
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  tensor(bool),
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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 output types. Casting to complex is not supported.