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[quant] conv_transpose1d / conv_transpose2d#40370

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[quant] conv_transpose1d / conv_transpose2d#40370
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@z-a-f z-a-f commented Jun 22, 2020 •
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Stack from ghstack:

Differential Revision: D22158979

[quant] conv_transpose2d
7b2f3a2 
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dr-ci Bot commented Jun 22, 2020 •
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💊 CI failures summary and remediations

As of commit 22e676a (more details on the Dr. CI page):

  • 1/1 failures introduced in this PR

🕵️ 1 new failure recognized by patterns

The following CI failures do not appear to be due to upstream breakages:

See CircleCI build pytorch_linux_backward_compatibility_check_test (1/1)

Step: "Run tests" (full log | diagnosis details | 🔁 rerun)

Sep 13 02:30:30 The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not. 
Sep 13 02:30:30 processing existing schema:  add_constant(__torch__.torch.classes._TorchScriptTesting._ElementwiseInterpreter _0, str _1, Tensor _2) -> (None _0) 
Sep 13 02:30:30 processing existing schema:  set_input_names(__torch__.torch.classes._TorchScriptTesting._ElementwiseInterpreter _0, str[] _1) -> (None _0) 
Sep 13 02:30:30 processing existing schema:  set_output_name(__torch__.torch.classes._TorchScriptTesting._ElementwiseInterpreter _0, str _1) -> (None _0) 
Sep 13 02:30:30 processing existing schema:  __call__(__torch__.torch.classes._TorchScriptTesting._ElementwiseInterpreter _0, Tensor[] _1) -> (Tensor _0) 
Sep 13 02:30:30 processing existing schema:  __getstate__(__torch__.torch.classes._TorchScriptTesting._ElementwiseInterpreter _0) -> ((str[], str?, Dict(str, Tensor), (str, str[], str)[]) _0) 
Sep 13 02:30:30 processing existing schema:  __setstate__(__torch__.torch.classes._TorchScriptTesting._ElementwiseInterpreter _0, (str[], str?, Dict(str, Tensor), (str, str[], str)[]) _1) -> (None _0) 
Sep 13 02:30:30 processing existing schema:  get(__torch__.torch.classes._TorchScriptTesting._LiteInterpreterTest _0, Tensor _1) -> (str _0) 
Sep 13 02:30:30 processing existing schema:  __getstate__(__torch__.torch.classes._TorchScriptTesting._LiteInterpreterTest _0) -> (int _0) 
Sep 13 02:30:30 processing existing schema:  __setstate__(__torch__.torch.classes._TorchScriptTesting._LiteInterpreterTest _0, int _1) -> (None _0) 
Sep 13 02:30:30 processing existing schema:  __init__(__torch__.torch.classes.dist_rpc.WorkerInfo _0, str _1, int _2) -> (None _0) 
Sep 13 02:30:30 The PR is introducing backward incompatible changes to the operator library. Please contact PyTorch team to confirm whether this change is wanted or not.  
Sep 13 02:30:30  
Sep 13 02:30:30 Broken ops: [ 
m2=0.5, float? n2=0, float? m3=0.5, float? start_warmup_multiplier=0.10000000000000001, int? constant_warmup_num_iter=10000000, int? linear_warmup_num_iter=10000000, float? cyclical_max_lr=0.050000000000000003, int? cyclical_step_size=1000000, float? cyclical_decay=0.999, float? cosine_min_lr=0.01, float? cosine_max_lr=0.050000000000000003, int? cosine_period=50, float? cosine_t_mult=1., float? cosine_lr_shrink=0.98999999999999999, Tensor[]? _caffe2_preallocated_outputs=None) -> (Tensor output) 
Sep 13 02:30:30 ] 
Sep 13 02:30:30 + cleanup 
Sep 13 02:30:30 + retcode=1 
Sep 13 02:30:30 + set +x 
Sep 13 02:30:30 =================== sccache compilation log =================== 
Sep 13 02:30:30 =========== If your build fails, please take a look at the log above for possible reasons =========== 
Sep 13 02:30:30 Compile requests                 0
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This comment has been revised 245 times.

@z-a-f z-a-f changed the title [quant] conv_transpose2d [quant] conv_transpose1d / conv_transpose2d Jun 22, 2020
@z-a-f z-a-f requested a review from jerryzh168 June 22, 2020 08:59
z-a-f pushed a commit that referenced this pull request Jun 22, 2020
[quant] conv_transpose1d / conv_transpose2d
4a6ada3 
ghstack-source-id: b46e3f3
Pull Request resolved: #40370
@z-a-f z-a-f requested a review from jamesr66a June 22, 2020 08:59
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z-a-f commented Jun 22, 2020 •
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UPDATE: Resolved!

There is a weird bug, that I was tracking the whole weekend -- would appreciate if someone could tell me what's wrong.

Here is repro code

import numpy as np
import torch
from torch import nn

torch.backends.quantized.engine = 'qnnpack'

B = 2
L = 24

iC = 1
oC = 2
kL = 1

strides = (1,)
pads = (0,)
o_pads = (0,)
dilations = (1,)
groups = 1

X = torch.randn(B, iC, L).to(torch.float)
W = torch.randn(iC, oC // groups, kL)

X_s = 1.2
X_zp = 0
X_dtype = torch.quint8

W_s = 0.2
W_zp = 0
W_dtype = torch.qint8

b = None

y_s = 4.2
y_zp = 0

#################

X_q = torch.quantize_per_tensor(X, X_s, X_zp, X_dtype)
W_q = torch.quantize_per_tensor(W, W_s, W_zp, W_dtype)

#################

kernel_size = kL,

conv_ref = nn.ConvTranspose1d(iC, oC, kernel_size, stride=strides, padding=pads,
                              output_padding=o_pads, groups=groups,
                              bias=(b is not None), dilation=dilations)

conv_ref.weight = nn.Parameter(W)
if b is not None:
  conv_ref.bias = nn.Parameter(b)

y_ref = conv_ref(X)
y_ref_dq = torch.quantize_per_tensor(y_ref, y_s, y_zp, X_dtype).int_repr()

#################
W_prepack = torch.ops.quantized.conv_transpose1d_prepack(W_q, b, strides, pads,
                                                         o_pads, dilations,
                                                         groups)
W_unpacked, bias = torch.ops.quantized.conv_transpose1d_unpack(W_prepack)

print(W_q.dequantize() - W_unpacked.dequantize())


#################

y_q = torch.ops.quantized.conv_transpose1d(X_q, W_prepack, y_s, y_zp).int_repr()

#################

print(y_ref_dq.to(torch.float) - y_q.to(torch.float))

print(
  f'''
    iC: {W.shape[0]}
    oC: {W.shape[1] * groups}
    k: {W.shape[2:]}
  '''
)

result for the difference is expected to have maximum 1-off (actually >1-off due to deconv), but it looks like the only the first iC channels in the output are correct. That means that if oC > iC, the rest of the channels are off :'(

Output:

tensor([[[0.],
         [0.]]])
tensor([[[  0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,
            0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,
            0.,   0.],
         [  0., -36.,   0.,   0.,   0., -36., -36.,   0., -36.,   0.,   0.,
            0.,   0.,   0., -36.,   0., -73., -73.,   0.,   0., -36., -36.,
            0.,   0.]],

        [[  0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,
            0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,
            0.,   0.],
         [  0., -36.,   0.,   0.,   0., -36.,   0.,   0.,   0.,   0.,   0.,
            0.,   0., -36.,   0.,   0., -36.,   0., -36.,   0.,   0.,   0.,
          -36.,   0.]]])

    iC: 1
    oC: 2
    k: torch.Size([1])

cc @jerryzh168 @jamesr66a @kimishpatel @supriyar

@z-a-f z-a-f requested a review from paulshaoyuqiao June 22, 2020 09:06
@z-a-f z-a-f mentioned this pull request Jun 22, 2020
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kimishpatel commented Jun 22, 2020

@z-a-f, I can't say without knowing the details of the op. I am assuming this does not fail with fbgemm backend.
One thing I can suggest is: Can you print raw y_q result and see what is there in the second channel? I am wondering if second channel is not populated at all. Additionally in your implementation you can perhaps zero out the output tensor to confirm if the second is not populated at all vs populated with wrong data.

Zafar added 10 commits June 23, 2020 14:53
Update on "[quant] conv_transpose1d / conv_transpose2d"
b90009c 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
fae6ded 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
7010baa 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
5bc0586 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
81cad4e 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
32d7da5 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
20afb0e 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
7e75b40 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
726558d 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
3a9ab5a 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
vkuzo
vkuzo reviewed Jul 22, 2020
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would it make sense to add a numerical correctness test in this PR?

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looks good. Should we add a numerical correctness test in this PR?

This was referenced Aug 12, 2020
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z-a-f commented Sep 2, 2020

looks good. Should we add a numerical correctness test in this PR?

Yes -- I had the tests, they accidentally were submitted as part of a different PR -- I will migrate them here

@z-a-f z-a-f requested a review from vkuzo September 3, 2020 00:22
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lg as long as CI passes. Can we include the context and the test plan in the PR summary before landing, since this is non-trivial?

Zafar added 6 commits September 10, 2020 15:08
Update on "[quant] conv_transpose1d / conv_transpose2d"
f336f85 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
b1b2208 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
e300acd 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
a2ec6fc 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
d3580fa 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
Update on "[quant] conv_transpose1d / conv_transpose2d"
22e676a 
Differential Revision: [D22158979](https://our.internmc.facebook.com/intern/diff/D22158979)

[ghstack-poisoned]
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facebook-github-bot commented Sep 15, 2020

@z-a-f merged this pull request in 9d4943d.

@facebook-github-bot facebook-github-bot deleted the gh/z-a-f/41/head branch September 18, 2020 14:17
xuzhao9 pushed a commit that referenced this pull request Sep 18, 2020
@xuzhao9
[quant] conv_transpose1d / conv_transpose2d (#40370)
65b3f2c 
Summary: Pull Request resolved: #40370

Test Plan: Imported from OSS

Reviewed By: vkuzo

Differential Revision: D22158979

Pulled By: z-a-f

fbshipit-source-id: f5cb812c9953efa7608f06cf0188de447f73f358
laurentdupin pushed a commit to laurentdupin/pytorch that referenced this pull request Apr 24, 2026
@facebook-github-bot
[quant] conv_transpose1d / conv_transpose2d (pytorch#40370)
3724255 
Summary: Pull Request resolved: pytorch#40370

Test Plan: Imported from OSS

Reviewed By: vkuzo

Differential Revision: D22158979

Pulled By: z-a-f

fbshipit-source-id: f5cb812c9953efa7608f06cf0188de447f73f358
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