Computes the "logical or" of elements across dimensions of a tensor. Reduces `input_tensor` along the dimensions given in `axis`. Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each entry in `axis`. If `keepdims` is true, the reduced dimensions are retained with lengt
(input_tensor, axis=None, keepdims=False, name=None)
| 2363 | @tf_export("math.reduce_any", "reduce_any", v1=[]) |
| 2364 | @dispatch.add_dispatch_support |
| 2365 | def reduce_any(input_tensor, axis=None, keepdims=False, name=None): |
| 2366 | """Computes the "logical or" of elements across dimensions of a tensor. |
| 2367 | |
| 2368 | Reduces `input_tensor` along the dimensions given in `axis`. |
| 2369 | Unless `keepdims` is true, the rank of the tensor is reduced by 1 for each |
| 2370 | entry in `axis`. If `keepdims` is true, the reduced dimensions |
| 2371 | are retained with length 1. |
| 2372 | |
| 2373 | If `axis` is None, all dimensions are reduced, and a |
| 2374 | tensor with a single element is returned. |
| 2375 | |
| 2376 | For example: |
| 2377 | |
| 2378 | ```python |
| 2379 | x = tf.constant([[True, True], [False, False]]) |
| 2380 | tf.reduce_any(x) # True |
| 2381 | tf.reduce_any(x, 0) # [True, True] |
| 2382 | tf.reduce_any(x, 1) # [True, False] |
| 2383 | ``` |
| 2384 | |
| 2385 | Args: |
| 2386 | input_tensor: The boolean tensor to reduce. |
| 2387 | axis: The dimensions to reduce. If `None` (the default), reduces all |
| 2388 | dimensions. Must be in the range `[-rank(input_tensor), |
| 2389 | rank(input_tensor))`. |
| 2390 | keepdims: If true, retains reduced dimensions with length 1. |
| 2391 | name: A name for the operation (optional). |
| 2392 | |
| 2393 | Returns: |
| 2394 | The reduced tensor. |
| 2395 | |
| 2396 | @compatibility(numpy) |
| 2397 | Equivalent to np.any |
| 2398 | @end_compatibility |
| 2399 | """ |
| 2400 | keepdims = False if keepdims is None else keepdims |
| 2401 | return _may_reduce_to_scalar( |
| 2402 | keepdims, axis, |
| 2403 | gen_math_ops._any( |
| 2404 | input_tensor, _ReductionDims(input_tensor, axis), keepdims, |
| 2405 | name=name)) |
| 2406 | |
| 2407 | |
| 2408 | @tf_export(v1=["math.reduce_logsumexp", "reduce_logsumexp"]) |
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