mindspore.ops.EmbeddingLookup
- class mindspore.ops.EmbeddingLookup[source]
Returns a slice of input tensor based on the specified indices.
This Primitive has the similar functionality as GatherV2 operating on axis = 0, but has one more inputs: offset.
- Inputs:
input_params (Tensor) - The shape of tensor is \((x_1, x_2, ..., x_R)\). This represents a Tensor slice, instead of the entire Tensor. Currently, the dimension is restricted to be 2.
input_indices (Tensor) - The shape of tensor is \((y_1, y_2, ..., y_S)\). Specifies the indices of elements of the original Tensor. Values can be out of range of input_params, and the exceeding part will be filled with 0 in the output. Values do not support negative and the result is undefined if values are negative. The data type should be int32 or int64.
offset (int) - Specifies the offset value of this input_params slice. Thus the real indices are equal to input_indices minus offset.
- Outputs:
Tensor, the shape of tensor is \((z_1, z_2, ..., z_N)\). The data type is the same with input_params.
- Raises
TypeError – If dtype of input_indices is not int.
ValueError – If length of shape of input_params is greater than 2.
- Supported Platforms:
Ascend
CPU
GPU
Examples
>>> input_params = Tensor(np.array([[8, 9], [10, 11], [12, 13], [14, 15]]), mindspore.float32) >>> input_indices = Tensor(np.array([[5, 2], [8, 5]]), mindspore.int32) >>> offset = 4 >>> output = ops.EmbeddingLookup()(input_params, input_indices, offset) >>> print(output) [[[10. 11.] [ 0. 0.]] [[ 0. 0.] [10. 11.]]]