fix at::from_blob_quantized_per_tensor_affine strides calculation

[yzyz]

Summary: There seems to be a off-by-one bug in at::from_blob_quantized_per_tensor_affine. For an input with sizes {N, C, H, W}, before strides would be calculated as {NCH, CH, H, 1}, now strides is calculated as {CHW, HW, W, 1}. The updated unit test catches this problem.

Test Plan:

buck test mode/dev-nosan //caffe2:quantized_test

before fix:

    ✓ ListingSuccess: caffe2:quantized_test : 9 tests discovered (15.632)
    ✓ Pass: caffe2:quantized_test - TestQTensor.QuantDequantAPIs (0.004)
    ✗ Fail: caffe2:quantized_test - TestQTensor.FromBlobQuantizedPerTensor (0.002)
Test output:
> caffe2/aten/src/ATen/test/quantized_test.cpp:247
Expected equality of these values:
  qtensor[h][w].item<float>()
    Which is: -0.5
  (custom_data[i] - zero_point) * scale
    Which is: 0

stdout: Note: Google Test filter = TestQTensor.FromBlobQuantizedPerTensor
[==========] Running 1 test from 1 test suite.
[----------] Global test environment set-up.
[----------] 1 test from TestQTensor
[ RUN      ] TestQTensor.FromBlobQuantizedPerTensor
caffe2/aten/src/ATen/test/quantized_test.cpp:247: Failure
Expected equality of these values:
  qtensor[h][w].item<float>()
    Which is: -0.5
  (custom_data[i] - zero_point) * scale
    Which is: 0
[  FAILED  ] TestQTensor.FromBlobQuantizedPerTensor (2 ms)
[----------] 1 test from TestQTensor (2 ms total)

[----------] Global test environment tear-down
[==========] 1 test from 1 test suite ran. (2 ms total)
[  PASSED  ] 0 tests.
[  FAILED  ] 1 test, listed below:
[  FAILED  ] TestQTensor.FromBlobQuantizedPerTensor

 1 FAILED TEST

after fix:

    ✓ ListingSuccess: caffe2:quantized_test : 9 tests discovered (16.051)
    ✓ Pass: caffe2:quantized_test - TestQTensor.RoundingMode (0.002)
    ✓ Pass: caffe2:quantized_test - TestQTensor.QuantizePerChannel4dChannelsLast (0.217)
    ✓ Pass: caffe2:quantized_test - TestQTensor.QuantDequantAPIs (0.003)
    ✓ Pass: caffe2:quantized_test - TestQTensor.EmptyPerchannelQuantized (0.003)
    ✓ Pass: caffe2:quantized_test - TestQTensor.EmptyQuantized (0.002)
    ✓ Pass: caffe2:quantized_test - TestQTensor.FromBlobQuantizedPerChannel (0.004)
    ✓ Pass: caffe2:quantized_test - TestQTensor.QuantizePerChannel4d (0.005)
    ✓ Pass: caffe2:quantized_test - TestQTensor.FromBlobQuantizedPerTensor (0.003)
    ✓ Pass: caffe2:quantized_test - TestQTensor.Item (0.002)
Summary
  Pass: 9
  ListingSuccess: 1

Differential Revision: D37061355

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This pull request was exported from Phabricator. Differential Revision: D37061355

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This pull request was exported from Phabricator. Differential Revision: D37061355

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@pytorchbot merge

(Initiating merge automatically since Phabricator Diff has merged)

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[github-actions]

Hey @yzyz.
You've committed this PR, but it does not have both a 'release notes: ...' and 'topics: ...' label. Please add one of each to the PR. The 'release notes: ...' label should represent the part of PyTorch that this PR changes (fx, autograd, distributed, etc) and the 'topics: ...' label should represent the kind of PR it is (not user facing, new feature, bug fix, perf improvement, etc). The list of valid labels can be found here for the 'release notes: ...' and here for the 'topics: ...'.
For changes that are 'topic: not user facing' there is no need for a release notes label.