test_topi_conv1d_transpose_ncw.py 3.78 KB
Newer Older
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you 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.
"""Test code for transposed convolution."""
import numpy as np
import itertools
import tvm
21
from tvm import te
22 23 24 25 26 27
import topi
import topi.testing
from tvm.contrib.pickle_memoize import memoize
from topi.util import get_const_tuple
from common import get_all_backend

28 29 30 31 32
_conv1d_transpose_ncw_implement = {
    "generic": (topi.nn.conv1d_transpose_ncw, topi.generic.schedule_conv1d_transpose_ncw),
    "gpu": (topi.cuda.conv1d_transpose_ncw, topi.cuda.schedule_conv1d_transpose_ncw)
}

33 34
def verify_conv1d_transpose_ncw(batch, in_channel, in_size, num_filter, kernel, stride, padding):
    in_width = in_size
35 36
    A = te.placeholder((batch, in_channel, in_width), name='A')
    W = te.placeholder((in_channel, num_filter, kernel), name='W')
37 38 39 40 41 42 43 44 45

    a_shape = get_const_tuple(A.shape)
    w_shape = get_const_tuple(W.shape)
    dtype = A.dtype

    @memoize("topi.tests.test_topi_conv1d_transpose.verify_conv1d_transpose_ncw")
    def get_ref_data():
        a_np = np.random.uniform(size=a_shape).astype(dtype)
        w_np = np.random.uniform(size=w_shape).astype(dtype)
46
        b_np = topi.testing.conv1d_transpose_ncw_python(a_np, w_np, stride, padding)
47 48 49 50 51 52 53 54 55 56 57
        c_np = np.maximum(b_np, 0)
        return a_np, w_np, b_np, c_np

    a_np, w_np, b_np, c_np = get_ref_data()

    def check_device(device):
        ctx = tvm.context(device, 0)
        if not ctx.exist:
            print("Skip because %s is not enabled" % device)
            return
        with tvm.target.create(device):
58 59
            fcompute, fschedule = topi.testing.dispatch(device, _conv1d_transpose_ncw_implement)
            B = fcompute(A, W, stride, padding, A.dtype)
60
            C = topi.nn.relu(B)
61 62
            s1 = fschedule([B])
            s2 = fschedule([C])
63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94
        a = tvm.nd.array(a_np, ctx)
        w = tvm.nd.array(w_np, ctx)
        b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=B.dtype), ctx)
        c = tvm.nd.array(np.zeros(get_const_tuple(C.shape), dtype=C.dtype), ctx)

        func1 = tvm.build(s1, [A, W, B], device)
        func2 = tvm.build(s2, [A, W, C], device)
        func1(a, w, b)
        func2(a, w, c)
        tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5)
        tvm.testing.assert_allclose(c.asnumpy(), c_np, rtol=1e-5)

    for device in get_all_backend():
        check_device(device)


def test_conv1d_transpose_ncw():
    verify_conv1d_transpose_ncw(1, 3, 224, 32, 5, 1, 0)
    verify_conv1d_transpose_ncw(1, 3, 224, 32, 7, 1, 2)
    verify_conv1d_transpose_ncw(1, 3, 224, 32, 5, 2, 1)
    verify_conv1d_transpose_ncw(1, 3, 224, 32, 5, 2, 0)
    verify_conv1d_transpose_ncw(1, 32, 32, 128, 5, 1, 0)
    verify_conv1d_transpose_ncw(1, 32, 32, 128, 5, 2, 1)
    verify_conv1d_transpose_ncw(1, 1, 1024, 1, 512, 1, 256)
    verify_conv1d_transpose_ncw(1, 1, 1024, 1, 512, 2, 256)
    verify_conv1d_transpose_ncw(1, 1, 1024, 1, 512, 5, 256)
    verify_conv1d_transpose_ncw(1, 1, 10, 1, 5, 1, (0,3))
    verify_conv1d_transpose_ncw(1, 1, 10, 1, 5, 1, (1,3))
    verify_conv1d_transpose_ncw(1, 1, 10, 1, 5, 1, (2,3))

if __name__ == "__main__":
    test_conv1d_transpose_ncw()