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fixed doc for merge 

fixed Embedding
This commit is contained in:
jiangjinsheng 2020-06-02 14:32:20 +08:00
parent 5cba231ba9
commit 00e05f7c34
2 changed files with 6 additions and 4 deletions
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8
mindspore/nn/layer/embedding.py
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@ -44,10 +44,11 @@ class Embedding(Cell):
dtype (:class:`mindspore.dtype`): Data type of input. Default: mindspore.float32. dtype (:class:`mindspore.dtype`): Data type of input. Default: mindspore.float32.
Inputs: Inputs:
- **input** (Tensor) - Tensor of shape :math:`(\text{vocab_size})`. - **input** (Tensor) - Tensor of shape :math:`(\text{batch_size}, \text{input_length})`. The element of
the Tensor should be integer and not larger than vocab_size. else the corresponding embedding vector is zero
if larger than vocab_size.
Outputs: Outputs:
Tensor of shape :math:`(\text{vocab_size}, \text{embedding_size})`. Tensor of shape :math:`(\text{batch_size}, \text{input_length}, \text{embedding_size})`.
Examples: Examples:
>>> net = nn.Embedding(20000, 768, True) >>> net = nn.Embedding(20000, 768, True)
@ -61,6 +62,7 @@ class Embedding(Cell):
def __init__(self, vocab_size, embedding_size, use_one_hot=False, embedding_table='normal', dtype=mstype.float32): def __init__(self, vocab_size, embedding_size, use_one_hot=False, embedding_table='normal', dtype=mstype.float32):
super(Embedding, self).__init__() super(Embedding, self).__init__()
validator.check_subclass("dtype", dtype, mstype.number_type, self.cls_name) validator.check_subclass("dtype", dtype, mstype.number_type, self.cls_name)
validator.check_value_type('use_one_hot', use_one_hot, [bool], self.cls_name)
self.vocab_size = vocab_size self.vocab_size = vocab_size
self.embedding_size = embedding_size self.embedding_size = embedding_size
self.use_one_hot = use_one_hot self.use_one_hot = use_one_hot

2
mindspore/ops/operations/control_ops.py
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@ -144,7 +144,7 @@ class Merge(PrimitiveWithInfer):
One and only one of the inputs should be selected as the output One and only one of the inputs should be selected as the output
Inputs: Inputs:
- **inputs** (Tuple) - The data to be merged. All tuple elements should have same data type. - **inputs** (Union(Tuple, List)) - The data to be merged. All tuple elements should have same data type.
Outputs: Outputs:
tuple. Output is tuple(`data`, `output_index`). The `data` has the same shape of `inputs` element. tuple. Output is tuple(`data`, `output_index`). The `data` has the same shape of `inputs` element.