test_primops.py

# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
#     http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import unittest
import numpy as np
import paddle
from paddle.incubate.autograd.primops import (
    neg, set_value, add, sub, mul, div, sqrt, tanh, reshape, broadcast,
    transpose, split, concat, reduce, matmul, slice_select, slice_assign,
    gather, scatter_add, fill_const)
from paddle.incubate.autograd.primx import Transform, topo_path, orig2prim, prim2orig, _gradients
from paddle.incubate.autograd.utils import enable_prim, disable_prim, prim_enabled


class TestPyPrimOps(unittest.TestCase):
    """ Test Python wrappers of primitive ops. """

    def setUp(self):
        paddle.enable_static()

    def test_ops(self):
        A = np.random.rand(1)
        B = np.random.rand(2)
        C = np.random.rand(2, 3)
        D = np.random.rand(2, 3)
        E = np.random.rand(3, 2)

        a = paddle.static.data(name='A', shape=A.shape, dtype='float32')
        b = paddle.static.data(name='B', shape=B.shape, dtype='float32')
        c = paddle.static.data(name='C', shape=C.shape, dtype='float32')
        d = paddle.static.data(name='D', shape=D.shape, dtype='float32')
        e = paddle.static.data(name='E', shape=E.shape, dtype='float32')

        add_1 = add(a, a)
        self.assertEqual(add_1.dtype, a.dtype)
        self.assertEqual(add_1.shape, a.shape)

        add_2 = add(c, d)
        self.assertEqual(add_2.dtype, c.dtype)
        self.assertEqual(add_2.shape, c.shape)

        sub_1 = sub(c, d)
        self.assertEqual(sub_1.dtype, c.dtype)
        self.assertEqual(sub_1.shape, c.shape)

        mul_1 = mul(c, d)
        self.assertEqual(mul_1.dtype, c.dtype)
        self.assertEqual(mul_1.shape, c.shape)

        div_1 = div(c, d)
        self.assertEqual(div_1.dtype, c.dtype)
        self.assertEqual(div_1.shape, c.shape)

        sqrt_1 = sqrt(b)
        self.assertEqual(sqrt_1.dtype, b.dtype)
        self.assertEqual(sqrt_1.shape, b.shape)

        tanh_1 = tanh(d)
        self.assertEqual(tanh_1.dtype, d.dtype)
        self.assertEqual(tanh_1.shape, d.shape)

        reshape_1 = reshape(c, d.shape)
        self.assertEqual(reshape_1.dtype, c.dtype)
        self.assertEqual(reshape_1.shape, d.shape)

        broadcast_1 = broadcast(b, e.shape)
        self.assertEqual(broadcast_1.dtype, b.dtype)
        self.assertEqual(broadcast_1.shape, e.shape)

        transpose_1 = transpose(c, axis=[1, 0])
        self.assertEqual(transpose_1.dtype, c.dtype)
        self.assertEqual(transpose_1.shape, e.shape)

        split_1_0, split_1_1 = split(c, num_or_sections=[1, 2], axis=1)
        self.assertEqual(split_1_0.dtype, c.dtype)
        self.assertEqual(split_1_0.shape, (2, 1))
        self.assertEqual(split_1_1.shape, (2, 2))

        concat_1 = concat([c, d], axis=0)
        self.assertEqual(concat_1.dtype, c.dtype)
        self.assertEqual(concat_1.shape, (4, 3))

        reduce_1 = reduce(d, axis=[1])
        self.assertEqual(reduce_1.dtype, d.dtype)
        self.assertEqual(reduce_1.shape, (2, ))

        reduce_2 = reduce(c, axis=[0, 1])
        self.assertEqual(reduce_2.dtype, c.dtype)
        self.assertEqual(reduce_2.shape, (1, ))
        # TODO: reduce + keepdim

        matmul_1 = matmul(d, e)
        self.assertEqual(matmul_1.dtype, d.dtype)
        self.assertEqual(matmul_1.shape, (2, 2))

        slice_select_1 = slice_select(
            e, axis=[0], starts=[0], ends=[2], strides=[1])
        self.assertEqual(slice_select_1.dtype, e.dtype)
        self.assertEqual(slice_select_1.shape, (2, 2))

        slice_select_2 = slice_select(
            d, axis=[0, 1], starts=[0, 1], ends=[2, 3], strides=[1, 2])
        self.assertEqual(slice_select_2.dtype, d.dtype)
        self.assertEqual(slice_select_2.shape, (2, 1))

        y = broadcast(b, [2, 2])
        slice_assign_1 = slice_assign(
            d, y, axis=[1], starts=[1], ends=[3], strides=[1])
        self.assertEqual(slice_assign_1.dtype, d.dtype)
        self.assertEqual(slice_assign_1.shape, d.shape)

        index = paddle.static.data('index', shape=[5], dtype='int32')
        gather_1 = gather(e, index, axis=0)
        self.assertEqual(gather_1.dtype, e.dtype)
        self.assertEqual(gather_1.shape, (5, 2))

        y = paddle.rand([5, 2], dtype='float32')
        scatter_add_1 = scatter_add(e, y, index, axis=0)
        self.assertEqual(scatter_add_1.dtype, e.dtype)
        self.assertEqual(scatter_add_1.shape, e.shape)

        fill_const_1 = fill_const(value=10, shape=a.shape, dtype=a.dtype)
        self.assertEqual(fill_const_1.shape, a.shape)
        self.assertEqual(fill_const_1.dtype, a.dtype)

        neg_1 = neg(x=b)
        self.assertEqual(neg_1.shape, b.shape)
        self.assertEqual(neg_1.dtype, b.dtype)

        set_value_1 = set_value(
            d, a, axis=[1], starts=[1], ends=[3], strides=[1], out=d)
        self.assertEqual(set_value_1.shape, d.shape)
        self.assertEqual(set_value_1.dtype, d.dtype)


if __name__ == '__main__':
    unittest.main()