test_topi_conv2d_nhwc_pack_int8.py 3.01 KB
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# 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.
"""Example code to do convolution."""
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import pytest
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import numpy as np
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import tvm
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from tvm import te
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from tvm import autotvm
from tvm.autotvm.task.space import FallbackConfigEntity
import topi
import topi.testing
from tvm.contrib.pickle_memoize import memoize
from topi.util import get_const_tuple


def verify_conv2d_1x1_nhwc_pack_int8(batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation=1):
    in_height = in_width = in_size

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    A = te.placeholder((batch, in_height, in_width, in_channel), name='A', dtype='uint8')
    W = te.placeholder((kernel, kernel, in_channel, num_filter), name='W', dtype='int8')
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    a_shape = get_const_tuple(A.shape)
    w_shape = get_const_tuple(W.shape)
    adtype = A.dtype
    wdtype = W.dtype

    @memoize("topi.tests.test_topi_conv2d_1x1_nhwc_pack_int8.verify_nhwc.v2")
    def get_ref_data():
        a_np = np.random.uniform(size=a_shape).astype(adtype)
        w_np = np.random.uniform(size=w_shape).astype(wdtype)
        dw_np = topi.testing.dilate_python(w_np, (dilation, dilation, 1, 1))
        b_np = topi.testing.conv2d_nhwc_python(a_np, dw_np, stride, padding)
        return a_np, w_np, b_np

    a_np, w_np, b_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
        print("Running on target: %s" % device)

        with tvm.target.create(device):
            B = topi.nn.conv2d(A, W, stride, padding, dilation, layout='NHWC', out_dtype="int32")
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            s = topi.x86.schedule_conv2d_nhwc_pack_int8([B])
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        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)
        func = tvm.build(s, [A, W, B], device)
        func(a, w, b)
        tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5)

    # for device in ['llvm -mcpu=skylake-avx512']:
    for device in ['llvm']:
        check_device(device)


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# TODO(@llyfacebook): Please fix https://github.com/apache/incubator-tvm/issues/4122 to enable this test.
@pytest.mark.skip
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def test_conv2d_nhwc():
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    verify_conv2d_1x1_nhwc_pack_int8(1, 256, 32, 256, 1, 1, 0)
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if __name__ == "__main__":
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    # test_conv2d_nhwc()
    pass