64 lines
2.2 KiB
64 lines
2.2 KiB
import paddle.v2.framework.core as core
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import unittest
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import numpy
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from paddle.v2.framework.op import Operator
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class OpTestMeta(type):
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"""
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Operator Test ClassMeta.
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It injects `test_all` method into user's OperatorTest class, to make Python
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unittest module run that method.
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The `test_all` read what value is stored in `self`. It use self's values to
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create and run a operator, and check whether that op is OK or not.
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See `test_add_two_op` for example usage.
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"""
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def __new__(cls, name, bases, attrs):
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obj = super(OpTestMeta, cls).__new__(cls, name, bases, attrs)
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def test_all(self):
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scope = core.Scope()
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kwargs = dict()
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places = [core.CPUPlace()]
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if core.is_compile_gpu():
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places.append(core.GPUPlace(0))
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for place in places:
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for in_name in Operator.get_op_input_names(self.type):
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if hasattr(self, in_name):
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kwargs[in_name] = in_name
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var = scope.new_var(in_name).get_tensor()
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arr = getattr(self, in_name)
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var.set_dims(arr.shape)
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var.set(arr, place)
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else:
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kwargs[in_name] = "@EMPTY@"
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for out_name in Operator.get_op_output_names(self.type):
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if hasattr(self, out_name):
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kwargs[out_name] = out_name
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scope.new_var(out_name).get_tensor()
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for attr_name in Operator.get_op_attr_names(self.type):
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if hasattr(self, attr_name):
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kwargs[attr_name] = getattr(self, attr_name)
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op = Operator(self.type, **kwargs)
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op.infer_shape(scope)
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ctx = core.DeviceContext.create(place)
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op.run(scope, ctx)
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for out_name in Operator.get_op_output_names(self.type):
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actual = numpy.array(scope.find_var(out_name).get_tensor())
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expect = getattr(self, out_name)
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numpy.isclose(actual, expect)
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obj.test_all = test_all
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return obj
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