[GitHub] [incubator-mxnet] MoisesHer commented on a change in pull request #20283: [v1.x] ONNX export for large model

[GitBox <gi...@apache.org>]

MoisesHer commented on a change in pull request #20283:
URL: https://github.com/apache/incubator-mxnet/pull/20283#discussion_r637181015



##########
File path: python/mxnet/onnx/README.md
##########
@@ -63,6 +63,9 @@ Parameters:
         This is the old name of in_types. We keep this parameter name for backward compatibility
     input_shape : List of tuple
         This is the old name of in_shapes. We keep this parameter name for backward compatibility
+    large_model : Boolean
+        Whether to export a model that is larger than 2 GB. If true will save param tensors in seperate

Review comment:
       typo: seperate -> separate

##########
File path: python/mxnet/onnx/mx2onnx/_export_model.py
##########
@@ -83,6 +83,9 @@ def export_model(sym, params, in_shapes=None, in_types=np.float32,
         This is the old name of in_types. We keep this parameter name for backward compatibility
     input_shape : List of tuple
         This is the old name of in_shapes. We keep this parameter name for backward compatibility
+    large_model : Boolean
+        Whether to export a model that is larger than 2 GB. If true will save param tensors in seperate

Review comment:
       typo:  seperate -> separate

##########
File path: python/mxnet/onnx/README.md
##########
@@ -75,6 +78,9 @@ When the model has multiple inputs, all the input shapes and dtypes must be prov
 #### Dynamic Shape Input
 We can set `dynamic=True` to turn on support for dynamic input shapes. Note that even with dynamic shapes, a set of static input shapes still need to be specified in `in_shapes`; on top of that, we'll also need to specify which dimensions of the input shapes are dynamic in `dynamic_input_shapes`. We can simply set the dynamic dimensions as `None`, e.g. `(1, 3, None, None)`, or use strings in place of the `None`'s for better understandability in the exported onnx graph, e.g. `(1, 3, 'Height', 'Width')`
 
+#### Export Large Model
+Uses can set `large_model=True` to exoprt models that are larger than 2GB. In this case, all parameter tensors will be saved into seperate files along with the .onnx model file.

Review comment:
       typo: exoprt -> export, seperate -> separate




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