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Huihuang Zheng cf43a321a8 [Dy2stat] Refactoring tensor_shape_transformer.py to Fix Change after Assign Bug (#31082 ) Problem In our old shape transformer logic, if user write: ``` s = tensor.shape ... y = paddle.some_api(s) ``` Dy2stat will change it to ``` ... y = paddle.some_api(convert_var_shape(tensor)) ``` However it will cause fatal bug if user changes the shape of `x` after assign. For example: ``` s = tensor.shape ... tensor = paddle.some_change_shape_api(tensor) ... y = paddle.some_api(s) ``` Then the Dy2stat will get wrong result because the code is translated into: ``` tensor = paddle.some_change_shape_api(tensor) ... y = paddle.some_api(convert_var_shape(tensor)) # tensor shape has been changed, not origin `s` value ``` Solution Logic It can not be solved in the old logic, so I refactoring tensor_shape_transformer logic. Now we will use `s` to store shape attribute and generate a var `s__STATIC_CONVERT_VAR_SHAPE_SUFFIX` to store static shape API `shape(tensor)` ``` s = tensor.shape ... y = paddle.some_api(s) ``` Dy2stat will change it to ``` s = tensor.shape s__STATIC_CONVERT_VAR_SHAPE_SUFFIX = shape(tensor) ... y = paddle.some_api(choose_shape_attr_or_api(s, s__STATIC_CONVERT_VAR_SHAPE_SUFFIX )) ``` In this case, the code is consistent with origin dygraph meaning and it fixed the change after assign bug. Code Key Note To help reviewers, the key change of this PR is changing `self.name_to_var_shape` from "mapping name to shape node" to "mapping name to its STATIC_CONVERT_VAR_SHAPE_SUFFIX name", then if a variable name has the SUFFIX, we can choose to use attribute shape or shape api. Other changes go with the key change. Consideration The issue of this PR is that we store extra static `shape` API result, will it harms the speed of Dy2stat? In some cases it will, but we argue that the benefit would be greater than the cost. 1. The extra calling to static `shape` API will happen when coder assign among shape variables. Take the following dygraph code as an instance: ``` s1 = tensor.shape s2 = s1 s3 = s2 ... ``` Then we called extra static `shape` APIs again and again, however users seldom write code like this. 2. If the shape variable is used a lot, for example: ``` s = tensor.shape y1 = paddle.some_api1(s) y2 = paddle.some_api2(s) y3 = paddle.some_api3(s) ``` Our old logic will create 3 shape APIs but now just 1. This is more common user code pattern. In fact, if reviewers take a look at the current unit test in this PR, you could see the op numbers decrease after this PR. So we argue that this PR can also improve speed in this code pattern.	4 years ago
..
dy2static	[Dy2stat] Refactoring tensor_shape_transformer.py to Fix Change after Assign Bug (#31082 )	4 years ago
__init__.py	[Dy2stat] Add a decorator paddle.jit.not_to_static to support that not to convert a function in Dynamic-to-Static. (#29253 )	4 years ago

[Dy2stat] Refactoring tensor_shape_transformer.py to Fix Change after Assign Bug (#31082 )

**Problem**
In our old shape transformer logic, if user write:
```
s = tensor.shape
...
y = paddle.some_api(s)
```
Dy2stat will change it to
```
...
y = paddle.some_api(convert_var_shape(tensor))
```
However it will cause fatal bug if user changes the shape of `x` after assign. For example:
```
s = tensor.shape
...
tensor = paddle.some_change_shape_api(tensor)
...
y = paddle.some_api(s)
```
Then the Dy2stat will get wrong result because the code is translated into:
```
tensor = paddle.some_change_shape_api(tensor)
...
y = paddle.some_api(convert_var_shape(tensor)) # tensor shape has been changed, not origin `s` value
```

**Solution Logic**

It can not be solved in the old logic, so I refactoring tensor_shape_transformer logic. Now we will use `s` to store shape attribute and generate a var `s__STATIC_CONVERT_VAR_SHAPE_SUFFIX` to store static shape API `shape(tensor)`
```
s = tensor.shape
...
y = paddle.some_api(s)
```
Dy2stat will change it to
```
s = tensor.shape
s__STATIC_CONVERT_VAR_SHAPE_SUFFIX = shape(tensor)
...
y = paddle.some_api(choose_shape_attr_or_api(s, s__STATIC_CONVERT_VAR_SHAPE_SUFFIX ))
```
In this case, the code is consistent with origin dygraph meaning and it fixed the change after assign bug.

**Code Key Note**

To help reviewers, the key change of this PR is changing `self.name_to_var_shape` from "mapping name to shape node" to "mapping name to its STATIC_CONVERT_VAR_SHAPE_SUFFIX name", then if a variable name has the SUFFIX, we can choose to use attribute shape or shape api. Other changes go with the key change.

**Consideration**
The issue of this PR is that we store extra static `shape` API result, will it harms the speed of Dy2stat? In some cases it will, but we argue that the benefit would be greater than the cost.

1. The extra calling to static `shape` API will happen when coder assign among shape variables. Take the following dygraph code as an instance:
```
s1 = tensor.shape
s2 = s1
s3 = s2
...
```
Then we called extra static `shape` APIs again and again, however users seldom write code like this.

2. If the shape variable is used a lot, for example:
```
s = tensor.shape
y1 = paddle.some_api1(s)
y2 = paddle.some_api2(s)
y3 = paddle.some_api3(s)
```
Our old logic will create 3 shape APIs but now just 1. This is more common user code pattern. In fact, if reviewers take a look at the current unit test in this PR, you could see the op numbers decrease after this PR. So we argue that this PR can also improve speed in this code pattern.

dy2static

[Dy2stat] Refactoring tensor_shape_transformer.py to Fix Change after Assign Bug (#31082 )

__init__.py

[Dy2stat] Add a decorator paddle.jit.not_to_static to support that not to convert a function in Dynamic-to-Static. (#29253 )