- 17 12月, 2019 1 次提交
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由 HappyAngel 提交于
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- 13 12月, 2019 1 次提交
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由 hong19860320 提交于
[LITE][NPU][XPU] Refine subgraph pass, and support NPU/XPU model generation at execution time (#2576)
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- 10 12月, 2019 1 次提交
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由 yiicy 提交于
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- 08 12月, 2019 1 次提交
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由 liu zhengxi 提交于
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- 07 12月, 2019 1 次提交
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由 juncaipeng 提交于
* add arm split lod tensor, test=develop * add arm merge lod tensor, test=develop * update split merge lod tensor, test=develop * add reduce_prob op, test=develop * support mask_rcnn succeed, test=develop
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- 06 12月, 2019 1 次提交
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由 Wilber 提交于
- fix fill_constant bug. - cast op support int64_t->int32_t
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- 04 12月, 2019 1 次提交
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由 Wilber 提交于
update cuda kernels to run content-dnn model
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- 29 11月, 2019 1 次提交
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由 zhupengyang 提交于
test=develop
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- 28 11月, 2019 2 次提交
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由 zhupengyang 提交于
test=develop
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由 yiicy 提交于
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- 27 11月, 2019 1 次提交
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由 myq406450149 提交于
* fill_constant can support shape is tensor or tensorlist
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- 26 11月, 2019 2 次提交
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由 huzhiqiang 提交于
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由 zhupengyang 提交于
* [XPU] update conv padding test=develop * [XPU] exclude xpu for passes test=develop * fix conv padding compute test=develop * [NPU] update 2-pad to 4-pad for conv and conv_transpose test=develop * reuse UpdatePadding code test=develop
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- 25 11月, 2019 4 次提交
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由 HappyAngel 提交于
fix ccompute shape error in ooperators/conv_op.h, test=develop
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由 huzhiqiang 提交于
* arrange ops&kernels to support basic models * add relu and iocopy into basic * add fusion_elementwise_activation_ops into basic * add dropout,layout,io_copyonce kernel&op into basic
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由 Wilber 提交于
* update x86 op and kernel to run content-dnn model test=develop
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由 myq406450149 提交于
* split op upgrade
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- 22 11月, 2019 2 次提交
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由 HappyAngel 提交于
* fix conv 2-pad to 4-pad * fix compute conv shape * fix pad, test=develop * change conv_depthwise_3x3s1_fp.cc name to conv3x3s1p01_depthwise_fp32.cc to distinguish between conv3x3s1_depthwise_fp32.cc * delete printf note in conv3x3s1, test=develop * delete printf note, test=develop * delete gem_sdot.h, test=develop it is coped from __gemm_sdot_meta_.h * update compute padding, test=develop * fix padding size, must be 2 or 4. test=develop * fix format in operators/conv_op.cc, test=develop * change #if 0 to #if 1, test=develop * put 2-pad to 4-pad in AttachImpl, test=develop * fix clang-format error inn tests/math/connv_compute_test, test=develop * fix x86 test result error, test=develop * add asymmetric padding test case in liite/tests/math/conv_compute.cc, test=develop * change paddings type to support dynamically modify, test=develop * fix x86 build error in connv_compute_test, test=develop * fix opencl build error, test=develop * fix oopencl build error, test=develop * fix opencl/conv_compute build error, test=develop * fix opencl/conv_compute build error, test=develop * fix format in kernels/opencl/conv_computte_ttest,test=develop * fix build error, test=develop fix build error in kernels/x86/conv_compute.h
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由 HappyAngel 提交于
* fix pooling bug and speed * fix build error * delete VLOGin pool, test=develop * add openmp, test=develop * fix lite/kernels/arm/pool_compute_test basic_pooling compute error bug, test=develop * update pooling 2-pad to 4-pad, test=develop * fix 2-pad to 4-pad in operators/pool_op.h, AttachKernel will set param, so 2-pad to 4-pad funcs should put in AttachKernel. test=ddevellop * put 2-pad to 4-pad in AttachImpl, test=develop * according to reviews, fix some format error. test=develop * fix format errorr, add (). test=develop * change paddings type to support dynamically modify, test=develop * update padding type int other devices, test=develop * fix x8d build error on shared_ptr, test=ddevelop * fix formmat in operators pool_op.cc, test=develop
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- 19 11月, 2019 4 次提交
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由 yiicy 提交于
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由 zhupengyang 提交于
test=develop
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由 huzhiqiang 提交于
* add x86 op and kernel : search_fc and sequence_topk_avg_pooling for content-dnn model test=develop
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由 zhupengyang 提交于
* [X86] add attention_padding_mask op, x86 kernel and unit test test=develop * [CUDA] add attention_padding_mask cuda kernel and unit test test=develop
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- 18 11月, 2019 3 次提交
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由 Wilber 提交于
- add var_conv_2d cuda kernel - add var_conv_2d cuda kernel unit test - temporarily set to two input mode, remove input(ROW) and input(COLUMN)
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由 Pei Yang 提交于
add search_group_padding op and x86 kernel
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由 zhupengyang 提交于
* [X86][CUDA] add sequence_arithmetic op , x86 kernel, cuda kernel and unit test test=develop * add sequence_arithmetic cuda kernel unit test test=develop
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- 16 11月, 2019 1 次提交
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由 hong19860320 提交于
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- 15 11月, 2019 1 次提交
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由 juncaipeng 提交于
* add search_seq_depadding x86 and cuda * add match_matrix_tensor x86 * add search_grnn x86, no test
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- 14 11月, 2019 3 次提交
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由 Wilber 提交于
- add var_conv_2d op - add var_conv_2d x86 kernel - add var_conv_2d x86 test
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由 liu zhengxi 提交于
* fix the compile error for cuda and fix unit test
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由 Pei Yang 提交于
* update lookup_table arm x86, test=develop * add lookup_table_v2_op for compatibility, test=develop
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- 13 11月, 2019 4 次提交
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由 Wilber 提交于
- add sequence_reverse op - add sequence_reverse kernel for x86 and cuda - add sequence_reverse_test for x86 and cuda
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由 Wilber 提交于
- add sequence_concat op - add sequence_concat kernel for x86 and cuda - add sequence_concat_test for x86 and cuda
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由 liu zhengxi 提交于
align the lite nearest, bilinear op to fluid on arm and cuda
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由 juncaipeng 提交于
* fix error for AxesTensorList in unsqueeze op
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- 12 11月, 2019 1 次提交
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由 juncaipeng 提交于
* update concat and unsqueeze, test=develop
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- 08 11月, 2019 1 次提交
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由 huzhiqiang 提交于
* move multiclass_nms kernel back to host test=develop * move layer_norm OP and arm_kernel into extra type since it's added after release/v2.0-beta1 and not related with CV test=develop * fix code_style test=develop
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- 07 11月, 2019 1 次提交
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由 huzhiqiang 提交于
We have changed 11 arm_kernels into extra type in #2347 , which has caused test_compiling failure. In this PR , we move their 11 related arm_kernel_test into build_extra=ON
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- 06 11月, 2019 2 次提交
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由 juncaipeng 提交于
* add channel_wise_dequantized_max_abs op and ChannelWiseDequantOpFuser, test=develop
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由 Wilber 提交于
update reshape op to support multiple input types of shape. priority: input(ShapeTensor) > input(Shape) > attr(shape) update slice op to support multiple iput types of starts and ends. priority: input(StartsTensor) > input(StartsTensorList) > attr(starts)
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