wehub-resource-sync
170 lines
6.4 KiB
Python
170 lines
6.4 KiB
Python
# Copyright (c) 2023 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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import unittest
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import paddle
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from paddle.base.core import call_vjp
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paddle.enable_static()
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def get_ir_divide_program():
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paddle.enable_static()
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main_program, start_program = (
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paddle.static.Program(),
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paddle.static.Program(),
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)
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with paddle.static.program_guard(main_program, start_program):
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x = paddle.tensor.fill_constant(
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shape=[1, 4], dtype='float32', value=2.0
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)
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x.stop_gradient = False
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y = paddle.tensor.fill_constant(shape=[4], dtype='float32', value=1.0)
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y.stop_gradient = False
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dout = paddle.tensor.fill_constant(
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shape=[1, 4], dtype='float32', value=1.0
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)
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dout.stop_gradient = False
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out = paddle.divide(x, y)
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return main_program
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def get_ir_sum_program():
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paddle.enable_static()
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main_program, start_program = (
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paddle.static.Program(),
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paddle.static.Program(),
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)
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with paddle.static.program_guard(main_program, start_program):
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x = paddle.tensor.fill_constant(
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shape=[4, 5], dtype='float32', value=2.0
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)
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x.stop_gradient = False
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dout = paddle.tensor.fill_constant(shape=[], dtype='float32', value=1.0)
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dout.stop_gradient = False
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out = paddle.sum(x)
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return main_program
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class TestVjpPrim(unittest.TestCase):
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def test_divide_grad_prim_case1(self):
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pir_program = get_ir_divide_program()
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paddle.framework.core._set_prim_backward_enabled(True)
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with paddle.pir_utils.IrGuard():
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dout = pir_program.global_block().ops[-2].result(0)
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out_grads = [[dout]]
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stop_gradients = [[False], [False]]
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divide_op = pir_program.global_block().ops[-1]
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with paddle.pir.core.program_guard(pir_program):
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grad_outs = call_vjp(
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divide_op,
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[[value] for value in divide_op.operands_source()],
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[[value] for value in divide_op.results()],
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out_grads,
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stop_gradients,
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)
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print(pir_program)
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reshape_op2 = pir_program.global_block().ops[-1]
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reshape_op1 = pir_program.global_block().ops[-2]
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self.assertEqual(len(grad_outs), 2)
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self.assertEqual(len(pir_program.global_block().ops), 11)
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self.assertTrue(reshape_op2.result(0).is_same(grad_outs[0][0]))
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self.assertTrue(reshape_op1.result(0).is_same(grad_outs[1][0]))
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paddle.framework.core._set_prim_backward_enabled(False)
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def test_divide_grad_no_prim(self):
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pir_program = get_ir_divide_program()
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paddle.framework.core._set_prim_backward_enabled(False)
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dout = pir_program.global_block().ops[-2].result(0)
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out_grads = [[dout]]
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stop_gradients = [[False], [False]]
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divide_op = pir_program.global_block().ops[-1]
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with paddle.pir.core.program_guard(pir_program):
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grad_outs = call_vjp(
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divide_op,
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[[value] for value in divide_op.operands_source()],
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[[value] for value in divide_op.results()],
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out_grads,
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stop_gradients,
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)
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self.assertEqual(len(grad_outs), 2)
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self.assertEqual(
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grad_outs[0][0].get_defining_op().name(), "pd_op.divide_grad"
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)
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self.assertEqual(
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grad_outs[1][0].get_defining_op().name(), "pd_op.divide_grad"
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)
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self.assertEqual(len(pir_program.global_block().ops), 5)
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def test_sum_grad_prim(self):
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pir_program = get_ir_sum_program()
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paddle.framework.core._set_prim_backward_enabled(True)
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with paddle.pir_utils.IrGuard():
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dout = pir_program.global_block().ops[-3].result(0)
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out_grads = [[dout]]
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stop_gradients = [[False]]
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sum_op = pir_program.global_block().ops[-1]
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with paddle.pir.core.program_guard(pir_program):
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grad_outs = call_vjp(
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sum_op,
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[[value] for value in sum_op.operands_source()],
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[[value] for value in sum_op.results()],
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out_grads,
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stop_gradients,
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)
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expand_op = pir_program.global_block().ops[-1]
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self.assertEqual(len(grad_outs), 1)
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self.assertEqual(len(pir_program.global_block().ops), 8)
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self.assertTrue(expand_op.result(0).is_same(grad_outs[0][0]))
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all_op_names = [
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"pd_op.full",
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"pd_op.full",
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"pd_op.full_int_array",
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"pd_op.sum",
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"pd_op.full_int_array",
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"pd_op.reshape",
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"pd_op.full_int_array",
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"pd_op.expand",
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]
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for idx, op in enumerate(pir_program.global_block().ops):
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self.assertEqual(op.name(), all_op_names[idx])
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paddle.framework.core._set_prim_backward_enabled(False)
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def test_sum_grad_no_prim(self):
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pir_program = get_ir_sum_program()
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paddle.framework.core._set_prim_backward_enabled(False)
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dout = pir_program.global_block().ops[-2].result(0)
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out_grads = [[dout]]
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stop_gradients = [[False]]
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sum_op = pir_program.global_block().ops[-1]
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with paddle.pir.core.program_guard(pir_program):
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grad_outs = call_vjp(
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sum_op,
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[[value] for value in sum_op.operands_source()],
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[[value] for value in sum_op.results()],
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out_grads,
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stop_gradients,
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)
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self.assertEqual(len(grad_outs), 1)
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self.assertEqual(
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grad_outs[0][0].get_defining_op().name(), "pd_op.sum_grad"
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)
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self.assertEqual(len(pir_program.global_block().ops), 5)
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if __name__ == "__main__":
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unittest.main()
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