Beispiel #1
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def meta_var_mean_correction(self, dim, *, correction, keepdim=False):
    dim = utils.reduction_dims(self.shape, dim)
    if keepdim:
        output_shape = tuple(self.shape[i] if i not in dim else 1 for i in range(self.ndim))
    else:
        output_shape = utils.compute_reduction_output_shape(self.shape, dim)
    result1 = self.new_empty(output_shape, dtype=toRealValueType(self.dtype))
    result2 = self.new_empty(output_shape)
    return result1, result2
Beispiel #2
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def _reduction_meta(inp, dims, *, output_dtype=None):
    """
    Meta function for single output reduction operations
    Stride logic is incorrect
    """
    assert isinstance(inp, TensorLike)
    if output_dtype is None:
        output_dtype = inp.dtype
    output_shape = utils.compute_reduction_output_shape(inp.shape, dims)
    return TensorMeta(shape=output_shape,
                      dtype=output_dtype,
                      device=inp.device)
Beispiel #3
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def meta_nanmedian(input):
    output_shape = utils.compute_reduction_output_shape(
        input.shape, tuple(range(input.dim()))
    )
    return input.new_empty(output_shape)
Beispiel #4
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def _compute_reduction_shape(self, dims, keepdim):
    if keepdim:
        return tuple(self.shape[i] if i not in dims else 1 for i in range(self.ndim))

    return utils.compute_reduction_output_shape(self.shape, dims)