4 examples of 'tensorflow reduce_sum' in Python

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176def reduce_sum(input_tensor, axis=None, keep_dims=False, name=None, reduction_indices=None):
177 tf.reduce_sum(input_tensor, axis, keep_dims, name, reduction_indices)
614def sum(self, x: BKTensor, *args: Any, **kwargs: Any) -> BKTensor:
615 return self.tf.reduce_sum(x, *args, **kwargs)
557def sum(x, axis=None, keepdims=False):
558 """Sum of the values in a tensor, alongside the specified axis.
559 """
560 return T.sum(x, axis=axis, keepdims=keepdims)
38def _SumGrad(op, grad):
39 """Gradient for Sum."""
40 # Fast path for when reducing to a scalar and ndims is known: adds only
41 # Reshape and Tile ops (and possibly a Shape).
42 if (op.inputs[0].get_shape().ndims is not None and
43 op.inputs[1].op.type == "Const"):
44 rank = op.inputs[0].get_shape().ndims
45 axes = tensor_util.MakeNdarray(op.inputs[1].op.get_attr("value"))
46 if np.array_equal(axes, np.arange(rank)): # Reduce all dims.
47 grad = array_ops.reshape(grad, [1] * rank)
48 # If shape is not fully defined (but rank is), we use Shape.
49 if op.inputs[0].get_shape().is_fully_defined():
50 input_shape = op.inputs[0].get_shape().as_list()
51 else:
52 input_shape = array_ops.shape(op.inputs[0])
53 return [array_ops.tile(grad, input_shape), None]
55 input_shape = array_ops.shape(op.inputs[0])
56 output_shape_kept_dims = math_ops.reduced_shape(input_shape, op.inputs[1])
57 tile_scaling = _safe_shape_div(input_shape, output_shape_kept_dims)
58 grad = array_ops.reshape(grad, output_shape_kept_dims)
59 return [array_ops.tile(grad, tile_scaling), None]

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