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tf.compat.v1.scatter_min
Reduces sparse updates into a variable reference using the min operation.
tf.compat.v1.scatter_min(
    ref, indices, updates, use_locking=False, name=None
)
  This operation computes
# Scalar indices
ref[indices, ...] = min(ref[indices, ...], updates[...])
# Vector indices (for each i)
ref[indices[i], ...] = min(ref[indices[i], ...], updates[i, ...])
# High rank indices (for each i, ..., j)
ref[indices[i, ..., j], ...] = min(ref[indices[i, ..., j], ...],
updates[i, ..., j, ...])
  This operation outputs ref after the update is done. This makes it easier to chain operations that need to use the reset value.
Duplicate entries are handled correctly: if multiple indices reference the same location, their contributions combine.
Requires updates.shape = indices.shape + ref.shape[1:] or updates.shape = [].
| Args | |
|---|---|
ref | 
      A mutable Tensor. Must be one of the following types: half, bfloat16, float32, float64, int32, int64. Should be from a Variable node. | 
     
indices | 
      A Tensor. Must be one of the following types: int32, int64. A tensor of indices into the first dimension of ref. | 
     
updates | 
      A Tensor. Must have the same type as ref. A tensor of updated values to reduce into ref. | 
     
use_locking | 
      An optional bool. Defaults to False. If True, the update will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention. | 
     
name | 
      A name for the operation (optional). | 
| Returns | |
|---|---|
A mutable Tensor. Has the same type as ref. | 
     
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
 https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/compat/v1/scatter_min