[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-371060094 @CodingCat I will read it. Thank you! This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-371059934 @pengzhao-intel Thank you! This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370730412 @marcoabreu Thank you:) I will commit it soon. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370681494 @marcoabreu Hello! Could you please retrigger the test? It seems that test_operator_gpu.test_deconv has some problem. And I have removed 'USE_STABLE_SORT_FOR_PROPOSAL' building flag. Thank you! This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370285916 @pengzhao-intel @xinyu-intel Thank you! I will have a try. The performance table name|time (ms) --|-- BBoxTransformInv|268 IoUTransformInv|Not used FilterBox|22 CopyScore|18 ReverseArgsort(unstable sort)|7303 ReorderProposals|338 nms(calculate area)|286 nms(calcuate nms)|7547 allocate memory for workspace|1 copy anchor to workspace_proposal|0 enumrate all shifted anchors|9 copy workspace_proposals_base to workspace_proposals|162 assign foreground scores for each anchor|45 prepare output|3 Total|16002 Using stable sort to sort anchors (ReverseArgsort) will increase about 3000 ms. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370285916 @pengzhao-intel @xinyu-intel Thank you! I will have a try. The performance table name|time (ms) --|-- Total|16002 BBoxTransformInv|268 IoUTransformInv|Not used FilterBox|22 CopyScore|18 ReverseArgsort(unstable sort)|7303 ReorderProposals|338 nms(calculate area)|286 nms(calcuate nms)|7547 allocate memory for workspace|1 copy anchor to workspace_proposal|0 enumrate all shifted anchors|9 copy workspace_proposals_base to workspace_proposals|162 assign foreground scores for each anchor|45 prepare output|3 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370285916 @pengzhao-intel @xinyu-intel Thank you! I will have a try. The performance table name|time (ms) --|-- Total|16002 BBoxTransformInv|268 IoUTransformInv|Not used FilterBox|22 CopyScore|18 ReverseArgsort(stable sort)|7303 ReorderProposals|338 nms(calculate area)|286 nms(calcuate nms)|7547 allocate memory for workspace|1 copy anchor to workspace_proposal|0 enumrate all shifted anchors|9 copy workspace_proposals_base to workspace_proposals|162 assign foreground scores for each anchor|45 prepare output|3 This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370447850 @marcoabreu The reason to add USE_STABLE_SORT_FOR_PROPOSAL flag is for the cpu/gpu consistency test. Proposal Operator (CPU) uses unstable sort to sort the anchors by scores, however Proposal Operator (GPU) uses stable sort. It leads to different outputs even if the code is right. For the performance, I couldn't replace unstable sort with stable sort in Proposal (CPU). And for the cpu/gpu consistency test, I think it's necessary to use a building flag to test these operators. Is there any better solution to test cpu/gpu consistency for Proposal? Thank you! I will modify the test case and change the building setting back. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370447850 @marcoabreu The reason to add USE_STABLE_SORT_FOR_PROPOSAL flag is for the cpu/gpu consistency test. Proposal Operator (CPU) uses unstable sort to sort the anchors by scores, however Proposal Operator (GPU) uses stable sort. It leads to different outputs even if the code is right. For the performance, I couldn't replace unstable sort with stable sort in Proposal (CPU). And for the cpu/gpu consistency test, I think it's necessary to use a building flag to test these operators. Is there any better solution to test cpu/gpu consistency for Proposal? Thank you! This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370447850 @marcoabreu The reason to add USE_STABLE_SORT_FOR_PROPOSAL flag is for the cpu/gpu consistency test. Proposal Operator (CPU) uses unstable sort to sort the anchors by scores, however Proposal Operator (GPU) uses stable sort. It leads to different outputs even if the code is right. For the performance, I couldn't replace unstable sort with stable sort in Proposal (CPU). And for the cpu/gpu consistency test, I think it's necessary to use a building flag to test these operators. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370447850 @marcoabreu The reason to add USE_STABLE_SORT_FOR_PROPOSAL flag is for the cpu/gpu consistency test. Proposal Operator (CPU) uses unstable sort to sort the anchors by scores, however Proposal Operator (GPU) uses stable sort. For the performance, I couldn't replace unstable sort with stable sort in Proposal (CPU). And for the cpu/gpu consistency test, I think it's necessary to use a building flag to test these operator. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370320488 For the cpu/gpu consistency test, it's interesting that the number of valid anchors in the CPU implementation and the GPU implementation may be different. The reason is that the float precision in CPU's and GPU's is different. The size of some anchors may be near the margin of the minimal valid anchor and overlap. The margin of the minimal valid anchor: https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L141 https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L159 Overlap: https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L273 I want to create testing sample to avoid these margins. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370320488 For the cpu/gpu consistency test, it's interesting that the number of valid anchors in the CPU implementation and the GPU implementation may be different. The reason is that the float precision in CPU's and GPU's is different. The size of some anchors may be near the margin of the minimal valid anchor or the maximal valid anchor. The margin of the minimal valid anchor: https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L159 The margin of the maximal valid anchor. https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L89 I want to create testing sample to avoid these margins. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370320488 For the cpu/gpu consistency, it's interesting that the number of valid anchors in the CPU implementation and the GPU implementation may be different. The reason is that the float precision in CPU's and GPU's is different. The size of some anchors may be near the margin of the minimal valid anchor or the maximal valid anchor. The margin of the minimal valid anchor: https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L159 The margin of the maximal valid anchor. https://github.com/wkcn/incubator-mxnet/blob/add_multi_proposal_cpu_version/src/operator/contrib/multi_proposal.cc#L89 I want to create testing sample to avoid these margins. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370285916 @pengzhao-intel @xinyu-intel Thank you! I will have a try. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369813766 @pengzhao-intel Thank you! I will have a try. ~~I use `#pragma omp paraller for` for each for-loop in Multi Proposal (cpu implementation), But the performance doesn't improve. Maybe it costs a little calculation.~~ This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370133350 @pengzhao-intel Here is the testing code. https://gist.github.com/wkcn/4a09c142bc9886b45b5a23461bbe4733 I found that I made a mistake that I didn't use `nd.waitall()` to test the performance. If not using `nd.waitall()`, the calculation will not execute because of lazy-evaluation. performance|CPU(no omp)|CPU(omp)|GPU -|---|---|- Time(s)|33.899|12.432|4.435 However, when I set the environment variables `MXNET_OMP_MAX_THREADS` or `OMP_NUM_THREADS`, it may bring bad performance. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-370133350 @pengzhao-intel Here is the testing code. https://gist.github.com/wkcn/4a09c142bc9886b45b5a23461bbe4733 I found that I made a mistake that I didn't use `nd.waitall()` to test the performance. If not using `nd.waitall()`, the calculation will not execute because of lazy-evaluation. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369813766 @pengzhao-intel Thank you! I will have a try. I use `#pragma omp paraller for` for each for-loop in Multi Proposal (cpu implementation), But the performance doesn't improve. Maybe it costs a little calculation. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369773050 @piiswrong Yes, I will add it. I found Proposal OP (CPU implementation) uses **unstable sort** (`std::sort`), https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cc#L195 and Proposal OP (GPU implementation) uses **stable sort** (`thrust::stable_sort_by_key`). https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cu#L517 And the accuracy of computation between CPU and GPU is different, it causes that NMS selects different boxes between CPU and GPU. When I replace `std::sort` with `std::stable_sort` in the CPU implementation, the cpu/gpu consistency test is passed. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369813766 @pengzhao-intel Thank you! I will have a try. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and
fix the bug in proposal op (gpu version)
URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369797499
I wrote a cpu/gpu consistency test for Proposal and MultiProposal.
I found there is difference between the CPU output and the GPU output for
mx.nd.contrib.Proposal.
It seems that the index order of the Non-Maximum-Suppression result may be
different between the CPU implementation and the GPU implementation.
And another problem is that it may need to add the condition `num_to_keep <
rpn_post_nms_top_n`
https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cu#L341
reference:
https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cc#L235
Here is the cpu/gpu consistency test.
```python
import mxnet as mx
import numpy as np
# @with_seed()
def test_multi_proposal_op():
# paramters
feature_stride = 16
scales = (8, 16, 32)
ratios = (0.5, 1, 2)
rpn_pre_nms_top_n = 12000
rpn_post_nms_top_n = 2000
threshold = 0.7
rpn_min_size = 16
feat_len = 14
H, W = feat_len, feat_len
num_anchors = len(scales) * len(ratios)
count_anchors = H * W * num_anchors
def get_new_data(batch_size, ctx):
'''
cls_prob: (batch_size, 2 * num_anchors, H, W)
bbox_pred: (batch_size, 4 * num_anchors, H, W)
im_info: (batch_size, 3)
'''
cls_prob = mx.nd.empty((batch_size, 2 * num_anchors, H, W), dtype =
np.float32, ctx = ctx)
bbox_pred = mx.nd.empty((batch_size, 4 * num_anchors, H, W), dtype =
np.float32, ctx = ctx)
im_info = mx.nd.empty((batch_size, 3), dtype = np.float32, ctx = ctx)
cls_prob = mx.nd.array(np.random.random(cls_prob.shape), ctx = ctx)
bbox_pred = mx.nd.array(np.random.random(bbox_pred.shape), ctx = ctx)
for i in range(batch_size):
im_size = np.random.randint(100, feat_len * feature_stride, size
= (2,))
im_scale = np.random.randint(70, 100) / 100.0
im_info[i, :] = [im_size[0], im_size[1], im_scale]
return cls_prob, bbox_pred, im_info
def check_proposal_consistency(op, batch_size):
'''
op is mx.nd.contrib.Proposal or mx.nd.contrib.MultiProposal
'''
cls_prob, bbox_pred, im_info = get_new_data(batch_size, mx.cpu(0))
rois_cpu, score_cpu = op(
cls_score = cls_prob,
bbox_pred = bbox_pred,
im_info = im_info,
feature_stride = feature_stride,
scales = scales,
ratios = ratios,
rpn_pre_nms_top_n = rpn_pre_nms_top_n,
rpn_post_nms_top_n = rpn_post_nms_top_n,
threshold = threshold,
rpn_min_size = rpn_min_size, output_score = True)
gpu_ctx = mx.gpu(0)
# copy data to gpu from cpu
cls_prob_gpu = cls_prob.as_in_context(gpu_ctx)
bbox_pred_gpu = bbox_pred.as_in_context(gpu_ctx)
im_info_gpu = im_info.as_in_context(gpu_ctx)
rois_gpu, score_gpu = op(
cls_score = cls_prob_gpu,
bbox_pred = bbox_pred_gpu,
im_info = im_info_gpu,
feature_stride = feature_stride,
scales = scales,
ratios = ratios,
rpn_pre_nms_top_n = rpn_pre_nms_top_n,
rpn_post_nms_top_n = rpn_post_nms_top_n,
threshold = threshold,
rpn_min_size = rpn_min_size, output_score = True)
print (rois_cpu.asnumpy(), rois_gpu.asnumpy())
assert np.allclose(rois_cpu.asnumpy(), rois_gpu.asnumpy())
assert np.allclose(score_cpu.asnumpy(), score_gpu.asnumpy())
check_proposal_consistency(mx.nd.contrib.Proposal, 1)
check_proposal_consistency(mx.nd.contrib.MultiProposal, 20)
test_multi_proposal_op()
print ("test ok")
```
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[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and
fix the bug in proposal op (gpu version)
URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369797499
I wrote a cpu/gpu consistency test for Proposal and MultiProposal.
I found there is difference between the CPU output and the GPU output for
mx.nd.contrib.Proposal.
It seems that the index order of the Non-Maximum-Suppression result may be
different.
And another problem is that it may need to add the condition `num_to_keep <
rpn_post_nms_top_n`
https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cu#L341
reference:
https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cc#L235
Here is the cpu/gpu consistency test.
```python
import mxnet as mx
import numpy as np
# @with_seed()
def test_multi_proposal_op():
# paramters
feature_stride = 16
scales = (8, 16, 32)
ratios = (0.5, 1, 2)
rpn_pre_nms_top_n = 12000
rpn_post_nms_top_n = 2000
threshold = 0.7
rpn_min_size = 16
feat_len = 14
H, W = feat_len, feat_len
num_anchors = len(scales) * len(ratios)
count_anchors = H * W * num_anchors
def get_new_data(batch_size, ctx):
'''
cls_prob: (batch_size, 2 * num_anchors, H, W)
bbox_pred: (batch_size, 4 * num_anchors, H, W)
im_info: (batch_size, 3)
'''
cls_prob = mx.nd.empty((batch_size, 2 * num_anchors, H, W), dtype =
np.float32, ctx = ctx)
bbox_pred = mx.nd.empty((batch_size, 4 * num_anchors, H, W), dtype =
np.float32, ctx = ctx)
im_info = mx.nd.empty((batch_size, 3), dtype = np.float32, ctx = ctx)
cls_prob = mx.nd.array(np.random.random(cls_prob.shape), ctx = ctx)
bbox_pred = mx.nd.array(np.random.random(bbox_pred.shape), ctx = ctx)
for i in range(batch_size):
im_size = np.random.randint(100, feat_len * feature_stride, size
= (2,))
im_scale = np.random.randint(70, 100) / 100.0
im_info[i, :] = [im_size[0], im_size[1], im_scale]
return cls_prob, bbox_pred, im_info
def check_proposal_consistency(op, batch_size):
'''
op is mx.nd.contrib.Proposal or mx.nd.contrib.MultiProposal
'''
cls_prob, bbox_pred, im_info = get_new_data(batch_size, mx.cpu(0))
rois_cpu, score_cpu = op(
cls_score = cls_prob,
bbox_pred = bbox_pred,
im_info = im_info,
feature_stride = feature_stride,
scales = scales,
ratios = ratios,
rpn_pre_nms_top_n = rpn_pre_nms_top_n,
rpn_post_nms_top_n = rpn_post_nms_top_n,
threshold = threshold,
rpn_min_size = rpn_min_size, output_score = True)
gpu_ctx = mx.gpu(0)
# copy data to gpu from cpu
cls_prob_gpu = cls_prob.as_in_context(gpu_ctx)
bbox_pred_gpu = bbox_pred.as_in_context(gpu_ctx)
im_info_gpu = im_info.as_in_context(gpu_ctx)
rois_gpu, score_gpu = op(
cls_score = cls_prob_gpu,
bbox_pred = bbox_pred_gpu,
im_info = im_info_gpu,
feature_stride = feature_stride,
scales = scales,
ratios = ratios,
rpn_pre_nms_top_n = rpn_pre_nms_top_n,
rpn_post_nms_top_n = rpn_post_nms_top_n,
threshold = threshold,
rpn_min_size = rpn_min_size, output_score = True)
print (rois_cpu.asnumpy(), rois_gpu.asnumpy())
assert np.allclose(rois_cpu.asnumpy(), rois_gpu.asnumpy())
assert np.allclose(score_cpu.asnumpy(), score_gpu.asnumpy())
check_proposal_consistency(mx.nd.contrib.Proposal, 1)
check_proposal_consistency(mx.nd.contrib.MultiProposal, 20)
test_multi_proposal_op()
print ("test ok")
```
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[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and
fix the bug in proposal op (gpu version)
URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369797499
I wrote a cpu/gpu consistency test for Proposal and MultiProposal.
I found there is difference between the CPU output and the GPU output for
mx.nd.contrib.Proposal.
It seems that the index order of Nonmaximum may be different.
And another problem is that it may need to add the condition `num_to_keep <
rpn_post_nms_top_n`
https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cu#L341
reference:
https://github.com/apache/incubator-mxnet/blob/master/src/operator/contrib/proposal.cc#L235
Here is the cpu/gpu consistency test.
```python
import mxnet as mx
import numpy as np
# @with_seed()
def test_multi_proposal_op():
# paramters
feature_stride = 16
scales = (8, 16, 32)
ratios = (0.5, 1, 2)
rpn_pre_nms_top_n = 12000
rpn_post_nms_top_n = 2000
threshold = 0.7
rpn_min_size = 16
feat_len = 14
H, W = feat_len, feat_len
num_anchors = len(scales) * len(ratios)
count_anchors = H * W * num_anchors
def get_new_data(batch_size, ctx):
'''
cls_prob: (batch_size, 2 * num_anchors, H, W)
bbox_pred: (batch_size, 4 * num_anchors, H, W)
im_info: (batch_size, 3)
'''
cls_prob = mx.nd.empty((batch_size, 2 * num_anchors, H, W), dtype =
np.float32, ctx = ctx)
bbox_pred = mx.nd.empty((batch_size, 4 * num_anchors, H, W), dtype =
np.float32, ctx = ctx)
im_info = mx.nd.empty((batch_size, 3), dtype = np.float32, ctx = ctx)
cls_prob = mx.nd.array(np.random.random(cls_prob.shape), ctx = ctx)
bbox_pred = mx.nd.array(np.random.random(bbox_pred.shape), ctx = ctx)
for i in range(batch_size):
im_size = np.random.randint(100, feat_len * feature_stride, size
= (2,))
im_scale = np.random.randint(70, 100) / 100.0
im_info[i, :] = [im_size[0], im_size[1], im_scale]
return cls_prob, bbox_pred, im_info
def check_proposal_consistency(op, batch_size):
'''
op is mx.nd.contrib.Proposal or mx.nd.contrib.MultiProposal
'''
cls_prob, bbox_pred, im_info = get_new_data(batch_size, mx.cpu(0))
rois_cpu, score_cpu = op(
cls_score = cls_prob,
bbox_pred = bbox_pred,
im_info = im_info,
feature_stride = feature_stride,
scales = scales,
ratios = ratios,
rpn_pre_nms_top_n = rpn_pre_nms_top_n,
rpn_post_nms_top_n = rpn_post_nms_top_n,
threshold = threshold,
rpn_min_size = rpn_min_size, output_score = True)
gpu_ctx = mx.gpu(0)
# copy data to gpu from cpu
cls_prob_gpu = cls_prob.as_in_context(gpu_ctx)
bbox_pred_gpu = bbox_pred.as_in_context(gpu_ctx)
im_info_gpu = im_info.as_in_context(gpu_ctx)
rois_gpu, score_gpu = op(
cls_score = cls_prob_gpu,
bbox_pred = bbox_pred_gpu,
im_info = im_info_gpu,
feature_stride = feature_stride,
scales = scales,
ratios = ratios,
rpn_pre_nms_top_n = rpn_pre_nms_top_n,
rpn_post_nms_top_n = rpn_post_nms_top_n,
threshold = threshold,
rpn_min_size = rpn_min_size, output_score = True)
print (rois_cpu.asnumpy(), rois_gpu.asnumpy())
assert np.allclose(rois_cpu.asnumpy(), rois_gpu.asnumpy())
assert np.allclose(score_cpu.asnumpy(), score_gpu.asnumpy())
check_proposal_consistency(mx.nd.contrib.Proposal, 1)
check_proposal_consistency(mx.nd.contrib.MultiProposal, 20)
test_multi_proposal_op()
print ("test ok")
```
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[GitHub] wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version)
wkcn commented on issue #9939: add multi proposal operator (cpu version) and fix the bug in proposal op (gpu version) URL: https://github.com/apache/incubator-mxnet/pull/9939#issuecomment-369773050 @piiswrong Yes, I will add it. This is an automated message from the Apache Git Service. To respond to the message, please log on GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
