piyushghai commented on a change in pull request #13597: [MXNET-1255] update
hybridize documentation
URL: https://github.com/apache/incubator-mxnet/pull/13597#discussion_r240440237
##########
File path: docs/tutorials/gluon/hybrid.md
##########
@@ -137,4 +137,94 @@ to gluon with `SymbolBlock`:
net2 = gluon.SymbolBlock.imports('model-symbol.json', ['data'],
'model-0001.params')
```
+## Operators that does not work with hybridize
+
+While most APIs are the same in NDArray and Symbol, there are some
differences. Writting `F.operator` and call `hybridize` may not work all the
time.
+Here we list all the APIs that do not work and provide you the work arounds.
+
+### Element-wise Operators
+
+The following arithmetic and comparison APIs are automatically broadcasted if
the input NDArrays have different shapes.
+However, that's not the case in Symbol API, it's not automatically broadcasted
and you have to manually specify whether to use element-wise operator or
broadcast operators.
+
+
+| NDArray APIs | Description |
+|---|---|
+|
[*NDArray.__add__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__add__)
| x.__add__(y) <=> x+y <=> mx.nd.add(x, y) |
+|
[*NDArray.__sub__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__sub__)
| x.__sub__(y) <=> x-y <=> mx.nd.subtract(x, y) |
+|
[*NDArray.__mul__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__mul__)
| x.__mul__(y) <=> x*y <=> mx.nd.multiply(x, y) |
+|
[*NDArray.__div__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__div__)
| x.__div__(y) <=> x/y <=> mx.nd.divide(x, y) |
+|
[*NDArray.__mod__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__mod__)
| x.__mod__(y) <=> x%y <=> mx.nd.modulo(x, y) |
+|
[*NDArray.__lt__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__lt__)
| x.__lt__(y) <=> x mx.nd.lesser(x, y) |
+|
[*NDArray.__le__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__le__)
| x.__le__(y) <=> x<=y <=> mx.nd.less_equal(x, y) |
+|
[*NDArray.__gt__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__gt__)
| x.__gt__(y) <=> x>y <=> mx.nd.greater(x, y) |
+|
[*NDArray.__ge__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__ge__)
| x.__ge__(y) <=> x>=y <=> mx.nd.greater_equal(x, y)|
+|
[*NDArray.__eq__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__eq__)
| x.__eq__(y) <=> x==y <=> mx.nd.equal(x, y) |
+|
[*NDArray.__ne__*](https://mxnet.incubator.apache.org/api/python/ndarray/ndarray.html#mxnet.ndarray.NDArray.__ne__)
| x.__ne__(y) <=> x!=y <=> mx.nd.not_equal(x, y) |
+
+The current workaround is to use corecponding broadcast operators for
arithmetic and comparison to avoid potential hybridization failure when input
shapes are different.
+
+| Symbol APIs | Description |
+|---|---|
+|[*broadcast_add*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_add)
| Returns element-wise sum of the input arrays with broadcasting. |
+|[*broadcast_sub*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_sub)
| Returns element-wise difference of the input arrays with broadcasting. |
+|[*broadcast_mul*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_mul)
| Returns element-wise product of the input arrays with broadcasting. |
+|[*broadcast_div*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_div)
| Returns element-wise division of the input arrays with broadcasting. |
+|[*broadcast_mod*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_mod)
| Returns element-wise modulo of the input arrays with broadcasting. |
+|[*broadcast_equal*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_equal)
| Returns the result of element-wise *equal to* (==) comparison operation with
broadcasting. |
+|[*broadcast_not_equal*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_not_equal)
| Returns the result of element-wise *not equal to* (!=) comparison operation
with broadcasting. |
+|[*broadcast_greater*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_greater)
| Returns the result of element-wise *greater than* (>) comparison operation
with broadcasting. |
+|[*broadcast_greater_equal*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_greater_equal)
| Returns the result of element-wise *greater than or equal to* (>=)
comparison operation with broadcasting. |
+|[*broadcast_lesser*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_lesser)
| Returns the result of element-wise *lesser than* (<) comparison
operation with broadcasting. |
+|[*broadcast_lesser_equal*](https://mxnet.incubator.apache.org/api/python/symbol/symbol.html#mxnet.symbol.broadcast_lesser_equal)
| Returns the result of element-wise *lesser than or equal to* (<=) comparison
operation with broadcasting. |
+
+For example, if you wan to add a NDarray to your input x, use `broadcast_add`
instead of `+`:
+
+```python
+def hybrid_forward(self, F, x):
+ # avoid writting: return x + F.ones((1, 1))
Review comment:
Same nit above :)
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
With regards,
Apache Git Services
