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Add quantized::convtranspose2d (#63914)

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Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/63914

Test Plan: Imported from OSS

Reviewed By: dreiss

Differential Revision: D30531889

fbshipit-source-id: a65e389da2722efbc62e3fe1edf503732326350d
This commit is contained in:
Akshit Khurana
2021-09-24 17:02:31 -07:00
committed by Facebook GitHub Bot
parent ab5eb56983
commit 1de8976e85
2 changed files with 9 additions and 14 deletions
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15
test/test_nnapi.py
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@ -540,13 +540,14 @@ class TestNNAPI(TestCase):
)
def test_conv2d_transpose(self):
torch.manual_seed(29)
in_ch, out_ch, kernel = (5, 7, (2, 2))
input_dim = (4, 5, 3, 3)
inp = torch.randn(input_dim)
convert_dims = input_dim[:2] + (0, 0)
for kind in ["float", "float-nhwc", "quant", "quant-nhwc"]:
with self.subTest(kind):
inp = torch.randn(input_dim)
model = torch.nn.ConvTranspose2d(in_ch, out_ch, kernel)
output_size = model(inp).numel()
atol_rtol = (0.0002, 0)
@ -554,20 +555,14 @@ class TestNNAPI(TestCase):
convert_arg = torch.zeros(*convert_dims)
if "quant" in kind:
# FIXME 'aten::slow_conv_transpose2d' with arguments from the 'QuantizedCPU' backend
continue
model = torch.nn.Sequential(model)
model.eval()
model = torch.nn.quantized.ConvTranspose2d(in_ch, out_ch, kernel)
model.qconfig = torch.quantization.get_default_qconfig('qnnpack')
model = torch.quantization.prepare(model)
model(inp)
model = torch.quantization.convert(model)
inp = qpt(inp, 1.0 / 16, 128)
# I've seen numerical differences between QNNPACK and NNAPI,
# but never more than 1 quantum, and never more than ~1% of
# but never more than 1 quantum, and never more than ~10% of
# the output in this test.
atol_rtol = (1, 0)
limit = output_size * 0.03
limit = output_size * 0.1
convert_arg = qpt(convert_arg, 1.0 / 16, 128)
if "nhwc" in kind: