[dy2static] Add print transformer and unify print format (#24068)
* add print transformer & unify print format, test=develop * remove using of dygraph_to_static_func, test=develop * remove python stdout capture, test=develop * fix compatibility problems for PY2, test=develop * fix detail error, test=develop * fix type analysis bug, test=develop * fix print tuple compatible error in PY2, test=develop * replace get_func to declarative, test=develop * fix detail bug, test=develop * fix some detail problems, test=develop * change visit_call in print transformer, test=developrevert-24314-dev/fix_err_msg
Chen Weihang
5 years ago
committed by
GitHub
parent
3e962aecc1
commit
9b851ba216
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import gast
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import astor
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from paddle.fluid.dygraph.dygraph_to_static.static_analysis import AstNodeWrapper, NodeVarType, StaticAnalysisVisitor
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class PrintTransformer(gast.NodeTransformer):
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"""
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This class transforms python print function to fluid.layers.Print.
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"""
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def __init__(self, wrapper_root):
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assert isinstance(
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wrapper_root, AstNodeWrapper
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), "Input non-AstNodeWrapper node for the initialization of PrintTransformer."
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self.wrapper_root = wrapper_root
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self.root = wrapper_root.node
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self.static_analysis_visitor = StaticAnalysisVisitor(self.root)
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self.node_to_wrapper_map = self.static_analysis_visitor.get_node_to_wrapper_map(
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)
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def transform(self):
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self.visit(self.root)
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# NOTE: deal with print in PY3
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def visit_Call(self, node):
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assert isinstance(node, gast.Call)
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if isinstance(node.func, gast.Name) and node.func.id == 'print':
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var = self._get_print_var(node)
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return self._construct_print_node(var)
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return node
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# NOTE: deal with print in PY2
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def visit_Print(self, node):
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var = self._get_print_var(node)
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print_call_node = self._construct_print_node(var)
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return gast.Expr(value=print_call_node)
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def _get_print_var(self, node):
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if isinstance(node, gast.Call):
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var_list = node.args
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elif isinstance(node, gast.Print):
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var_list = node.values
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if isinstance(var_list[0], gast.Tuple):
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var_list = var_list[0].elts
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# TODO: support print multiple Var
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assert len(var_list) == 1, "Now only support print one Variable."
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return var_list[0]
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def _construct_print_node(self, node):
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if isinstance(node, gast.Name):
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if self._is_tensor_node(node):
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print_node = gast.Call(
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func=gast.parse('fluid.layers.Print').body[0].value,
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args=[node],
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keywords=[])
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return print_node
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else:
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raise TypeError(
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"print object type error, only support print Variable now.")
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else:
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# TODO: may not only print with format
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raise NotImplementedError(
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"cannot transform print with format temporarily.")
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def _is_tensor_node(self, node):
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tensor_types = {NodeVarType.TENSOR, NodeVarType.PADDLE_RETURN_TYPES}
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wrapper_node = self.node_to_wrapper_map.get(node, None)
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if wrapper_node is not None:
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if wrapper_node.node_var_type & tensor_types:
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return True
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return False
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@ -0,0 +1,233 @@
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# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import numpy
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import unittest
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import paddle.fluid as fluid
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from paddle.fluid.dygraph.jit import declarative
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# 1. print VarBase
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@declarative
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def dyfunc_print_variable(x):
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"""
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PY2:
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Print(dest=None, values=[Name(id='x_v', annotation=None, type_comment=None)], nl=True)],
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PY3:
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Expr(
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value=Call(func=Name(id='print', annotation=None, type_comment=None),
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args=[Name(id='x_v', annotation=None, type_comment=None)],
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keywords=[]))
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"""
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# NOTE: transform to static code, var name will be changed
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x_v = fluid.dygraph.to_variable(x)
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print(x_v)
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# 2. print ndarray
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@declarative
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def dyfunc_print_ndarray(x):
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"""
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PY2:
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Print(dest=None, values=[Name(id='x', annotation=None, type_comment=None)
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PY3:
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Expr(
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value=Call(func=Name(id='print', annotation=None, type_comment=None),
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args=[Name(id='x', annotation=None, type_comment=None)],
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keywords=[]))
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"""
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print(x)
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# 3. print VarBase with format
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@declarative
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def dyfunc_print_with_format(x):
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"""
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PY2:
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Print(dest=None,
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values=[
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Call(
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func=Attribute(value=Constant(value='PrintVariable: {}', kind=None), attr='format'),
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args=[Name(id='x_v', annotation=None, type_comment=None)],
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keywords=[])],
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nl=True)
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PY3:
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Expr(
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value=Call(func=Name(id='print', annotation=None, type_comment=None),
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args=[
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Call(
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func=Attribute(value=Constant(value='PrintVariable: {}', kind=None), attr='format'),
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args=[Name(id='x_v', annotation=None, type_comment=None)],
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keywords=[])],
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keywords=[]))
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"""
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x_v = fluid.dygraph.to_variable(x)
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print("PrintVariable: {}".format(x_v))
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# 4. print VarBase with format 2
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@declarative
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def dyfunc_print_with_format2(x):
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"""
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PY2:
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Print(dest=None,
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values=[
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BinOp(left=Constant(value='PrintVariable: %s', kind=None),
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op=Mod,
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right=Name(id='x_v', annotation=None, type_comment=None))],
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nl=True)
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PY3:
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Expr(
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value=Call(func=Name(id='print', annotation=None, type_comment=None),
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args=[
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BinOp(left=Constant(value='PrintVariable: %s', kind=None),
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op=Mod,
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right=Name(id='x_v', annotation=None, type_comment=None))],
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keywords=[]))
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"""
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x_v = fluid.dygraph.to_variable(x)
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print("PrintVariable: %s" % (x_v))
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# 5. print VarBase in control flow1
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@declarative
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def dyfunc_print_with_ifelse(x):
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x_v = fluid.dygraph.to_variable(x)
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if len(x_v.shape) > 1:
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print(x_v)
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else:
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print(x_v)
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# 6. print mutiple VarBases
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@declarative
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def dyfunc_print_multi_vars(x):
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"""
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# NOTE: y_v type is error before cur PR in this case
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Assign(targets=[Name(id='y_v', annotation=None, type_comment=None)],
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value=BinOp(left=Name(id='x_v', annotation=None, type_comment=None), op=Mult, right=Constant(value=2, kind=None)))
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"""
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x_v = fluid.dygraph.to_variable(x)
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y_v = x_v * 2
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print(x_v)
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print(y_v)
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# 7. print continue VarBase
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@declarative
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def dyfunc_print_continue_vars(x):
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"""
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PY3:
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Expr(
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value=Call(func=Name(id='print', annotation=None, type_comment=None),
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args=[Name(id='x_v', annotation=None, type_comment=None),
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Name(id='y_v', annotation=None, type_comment=None)],
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keywords=[]))
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PY2:
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Print(dest=None,
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values=[
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Tuple(
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elts=[Name(id='x_v', annotation=None, type_comment=None),
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Name(id='y_v', annotation=None, type_comment=None)])],
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nl=True)
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"""
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x_v = fluid.dygraph.to_variable(x)
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y_v = x_v * 2
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print(x_v, y_v)
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class TestPrintBase(unittest.TestCase):
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def setUp(self):
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self.input = numpy.ones(5).astype("int32")
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self.place = fluid.CUDAPlace(0) if fluid.is_compiled_with_cuda(
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) else fluid.CPUPlace()
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self.set_test_func()
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def set_test_func(self):
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raise NotImplementedError("Print test should implement set_test_func")
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def get_dygraph_output(self):
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with fluid.dygraph.guard():
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self.dygraph_func(self.input)
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def get_static_output(self):
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with fluid.program_guard(fluid.Program()):
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# TODO: How to catch C++ stdout to python
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self.dygraph_func(self.input)
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class TestPrintVariable(TestPrintBase):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_variable
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def test_transformed_static_result(self):
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self.get_dygraph_output()
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self.get_static_output()
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class TestPrintNdArray(TestPrintBase):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_ndarray
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def test_transform_static_error(self):
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with self.assertRaises(TypeError):
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self.get_dygraph_output()
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self.get_static_output()
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class TestPrintWithFormat(TestPrintBase):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_format
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def test_transform_static_error(self):
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with self.assertRaises(NotImplementedError):
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self.get_dygraph_output()
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self.get_static_output()
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class TestPrintWithFormat2(TestPrintBase):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_format2
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def test_transform_static_error(self):
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with self.assertRaises(NotImplementedError):
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self.get_dygraph_output()
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self.get_static_output()
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class TestPrintWithIfElse(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_with_ifelse
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class TestPrintMultipleVar(TestPrintVariable):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_multi_vars
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class TestPrintContinueVar(TestPrintBase):
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def set_test_func(self):
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self.dygraph_func = dyfunc_print_continue_vars
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def test_transform_static_error(self):
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with self.assertRaises(AssertionError):
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self.get_dygraph_output()
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self.get_static_output()
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if __name__ == '__main__':
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unittest.main()
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