connorgoggins commented on a change in pull request #17599: Fixed Embedding op
for LT input
URL: https://github.com/apache/incubator-mxnet/pull/17599#discussion_r380334678
##########
File path: src/operator/tensor/indexing_op.h
##########
@@ -66,7 +66,7 @@ enum QuantizedEmbeddingOpResource {kTempSpace};
struct SparseEmbeddingParam: public dmlc::Parameter<SparseEmbeddingParam> {
- int input_dim;
+ index_t input_dim;
int output_dim;
Review comment:
@apeforest excellent point, there would be. For example, the following call
throws an error:
```
>>> mx.nd.Embedding(data=mx.nd.random_normal(shape=(1,)),
weight=mx.nd.random_normal(shape=(1,2**32)), input_dim=1, output_dim=2**32)
mxnet.base.MXNetError: MXNetError: Invalid Parameter format for output_dim
expect int but value='4294967296', in operator Embedding(name="",
output_dim="4294967296", input_dim="1")
```
With my latest update (changing the dtype of `output_dim` to `index_t`),
here is the result:
```
>>> mx.nd.Embedding(data=mx.nd.random_normal(shape=(1,)),
weight=mx.nd.random_normal(shape=(1,2**32)), input_dim=1, output_dim=2**32)
[[ 1.6323917 -0.33354783 -1.7378405 ... -0.36648417 0.6363522
2.367109 ]]
<NDArray 1x4294967296 @cpu(0)>
```
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