| c3fb81d018487e2e85dcdfa8abbb6ab76f1ceafe |
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30-May-2018 |
Miao Wang <miaowang@google.com> |
Guard concurrent scratch_buffer and gemmlowp::GemmContext access
- scrach_buffer is a file scoped static intended to minimize the
allocation cost for Conv2D computations when possible.
- In order to make it thread safe for multi-threaded execution,
we need to make sure no concucrrent access to it.
- Similarly for gemmlowp::GemmContext used in Conv2D and
FullyConnected.
- The mutex lock is added to prevent concurrent executions that may
access the static scratch buffer and static gemmlowp::GemmContext.
Bug: 80430825
Bug: 80465406
Test: NeuralNetworksTest_mt_static
Test: NeuralNetworksApiBenchmark no visible performance impact
Merged-In: I6b0df63a03d1f16a1e43a0c1062a997bfbe8f3f2
Change-Id: I6b0df63a03d1f16a1e43a0c1062a997bfbe8f3f2
(cherry picked from commit 9c63a9c428e5489bc8d118f52687a12206967208)
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 6e1812de773691c1a42dbc1d1906ca158a5d4951 |
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13-Apr-2018 |
Przemyslaw Szczepaniak <pszczepaniak@google.com> |
Fix Conv2D crash in 64bit binary.
tflite::optimized_ops::Conv uses signed int for offsets,
if the scratch buffer is larger than 0x7fff_ffff, it will
overflow and cause a segfault.
+ Added a flag for excluding tests depending on non-public api
Bug: 77982879
Test: NeuralNetworksTest
Change-Id: Ia5b561b626259bdcc5cbbb9482f0ae7dff8e345f
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 9447966379a4b3fba92f4dfda65aaba6b0482f1a |
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06-Apr-2018 |
Przemyslaw Szczepaniak <pszczepaniak@google.com> |
Make convFloat32 and convQuant8 not segfault when asking too much memory.
Added check for 32 bit overflow due to largish conv size for 32 bit
binaries. Added new[] operator return value check.
Fixed guard unique_ptr type from Type to Type[].
Test: NeuralNetworksTest
Bug: 73663843
Change-Id: Iab72337b7c78e79987b4f897393a05b34b4b79f9
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| eea11acb2a183642f0c5687b283f975844ea99c2 |
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28-Mar-2018 |
Przemyslaw Szczepaniak <pszczepaniak@google.com> |
Fix memory leak in convQuant8
convQuant8 is not freeing its heap allocated im2colData
buffer in case where GetQuantizedConvolutionMultipler or
QuantizeMultiplierSmallerThanOne was false.
Test: WIP, working on the test case, will upload shortly.
Bug: 73663843
Change-Id: I8a54f95d48f8c42734484b16f40069f43bb26e44
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| d9c5ba866bb0575cbb894c672e0a800844ccf6f8 |
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15-Dec-2017 |
Miao Wang <miaowang@google.com> |
Refactor CPU operations
- Share the same internal implementation as TF Lite.
Test: mm
Test: NeuralNetworksTest pass
Change-Id: I4f0f035087eca1d45d651249bd7f9933a5787bfe
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 8eb598abd0e77333688e97f7ed89b0dd60d144fa |
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29-Sep-2017 |
Miao Wang <miaowang@google.com> |
Allow Conv2D and FullyConnected use multiple thread.
Bug: 63905942
Test: mm
Test: NeuralNetworksTest pass
Change-Id: Iff6f248df4f33c296bb42cba1b68296ca301bf34
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 04e2cd01293be976ae5cdfd92588b9e1189392a0 |
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25-Sep-2017 |
Miao Wang <miaowang@google.com> |
Allow anisotropic strides for 2d conv and pooling operations.
- The original implementation forces stride_height == stride_width.
- This CL relaxes the restriction and allows anisotropic strides for
CONV_2D, DEPTHWISE_CONV_2D,
AVERAGE_POOL_2D, L2_POOL_2D, MAX_POOL_2D
Bug: 63905942
Test: mm
Test: NeuralNetworksTest pass
Change-Id: I6e941896501aa64b13d08774e4529e717ee756f0
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| be2b22578baf949d7be42ba002cee94304daf53c |
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22-Sep-2017 |
Miao Wang <miaowang@google.com> |
Use softer error reporting instead of CHECK*
- CHECK(x) checks whether condition x holds and LOG(FATAL) if not, which
will result in calling abort().
- This change uses nnOpsCheck which would log the failing condition and
return false to the runtime, allowing graceful failures.
Bug: 63905942
Test: NeuralNetworkTests pass
Change-Id: I8b1217f777638f974c91fa429449e39d37218af6
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 1b69ceeb5920503f18b6c6c1233b1fa481b6e634 |
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11-Sep-2017 |
Miao Wang <miaowang@google.com> |
Move all op preparation functions to OperationsUtils.
- All op operations are moved to OperationUtils.
- Add a helper function to derive implict padding scheme from
explicit paddings.
- Make all prepare function return false when seeing error.
Bug: 63905942
Test: NeuralNetworkTests
Change-Id: I16538dbd731a5ca1e6de5e0d0b269e9f386f4d29
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 6cd685f64bd82c003b8d0943fc6b7b8e0730b939 |
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10-Sep-2017 |
Miao Wang <miaowang@google.com> |
Making padding explicit, instead of SAME / VALID
- Use explicit padding {padding_left, padding_right, padding_top,
padding_bottom} for applicable ops.
- Updated the corresponding tests.
Bug: 63905942
Test: mm
Test: updated NeuralNetworkTest pass
Change-Id: Ifb8ccf59fbe5766dffe1537aa5357192a7c88a70
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 55cef2193279a646292fdeb355399627dd8990c8 |
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09-Sep-2017 |
Miao Wang <miaowang@google.com> |
Explicitly add "_2D" to applicable ops, and add fused activation
function enum.
- Add the fused activation enum to explicitly set the expectation that
only the included ones are supported for fused ops.
- Add "_2D" to CONV, DEPTHWISE_CONV, AVG_POOL, MAX_POOL, and L2_POOL,
since they are only supposed to do 2D computation.
- Updated the tests and the stack to plumbing the changes through.
Bug: 63905942
Test: mm
Test: NeuralNetworksTests pass for both CPU path and sample hidl driver.
Change-Id: I60aeabab1d193d26d938c0d1d3ffdd519740d222
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| 27e9be3904b034e422ee9b6ab70b35ea994d2b39 |
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03-Aug-2017 |
Miao Wang <miaowang@google.com> |
Initial implementation of the following quantized ops.
- CONV_QUANT8
- DEPTHWISE_CONV_QUANT8
- AVERAGE_POOL_QUANT8
- MAX_POOL_QUANT8
- LOGISTIC_QUANT8
Additionally, added functions to plumb through quantization
parameters.
Bug: 63905942
Test: mm
Test: end-to-end MobileNet quantized test pass
Change-Id: Ib2753c68bf2c51467ae1c158b45541bcfdf10789
/frameworks/ml/nn/common/operations/Conv2D.cpp
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| eb1f88846f147d1d80ee0d688fe4635b89a40ffa |
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26-Jul-2017 |
Miao Wang <miaowang@google.com> |
Implement the following operations for Android NN runtime.
- CONV_FLOAT32
- DEPTHWISE_CONV_FLOAT32
- AVERAGE_POOL_FLOAT32
- L2_POOL_FLOAT32
- MAX_POOL_FLOAT32
- RELU_FLOAT32
- RELU6_FLOAT32
- TANH_FLOAT32
- LOGISTIC_FLOAT32
Bug: 63905942
Test: mm
Test: End-to-end test with MobileNet pass
Change-Id: I3eaa9794c7cdffd01792d26c5d6497c8d56d8605
/frameworks/ml/nn/common/operations/Conv2D.cpp
|