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Convert PyTorch models via NNVM #23
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The unit tests are failing(https://neo-ai-ci.amazon-ml.com/blue/organizations/jenkins/tvm/detail/PR-23/5/pipeline):
Could you install torch at the beginning |
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def add_input(self, name, tensor): | ||
self.inputs[name] = PyTorchInput(name, tensor) | ||
self.inputs[name].graph = self |
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PyTorchInput
does not have property graph
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Yeah, I suppose we can set to None
by default. graph
is set by PyTorchGraph
in add_input
.
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def add_param(self, name, tensor): | ||
self.params[name] = PyTorchParam(name, tensor.astype('float32')) | ||
self.params[name].graph = self |
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PyTorchParam
does not have property graph
.
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Ditto
'stride': self._inputs[4].as_json(), | ||
} | ||
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# @property |
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remove dead code.
self.input_names = [self._input_name(0)] | ||
self.shape = self._inputs[1].as_json() | ||
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#def expand(node, *inputs): |
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remove dead code
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def __init__(self, node, graph): | ||
super(ATenOp, self).__init__(node, graph) | ||
self.dtype = 'float32' |
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Is float32 the only dtype?
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For simplicity, yes but we can add other datatypes, perhaps in a separate PR. DLR only supports float32.
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@property | ||
def shape(self): | ||
print('shape of', self.name) |
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Remove?
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yep thanks
print('shape of', self.name) | ||
if not hasattr(self, '_shape'): | ||
self._shape = list(infer_shape(create(self.as_nnvm()))[1][0]) | ||
print('got the shape') |
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Remove?
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@Laurawly @icemelon9 can you please take a look? Particularly at the topi implementation of adaptive pooling. Thanks! |
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@wweic seems PyTorch is still not installed (see CI results). Can you please investigate? |
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PoolType pool_type, | ||
const size_t height_axis, | ||
const size_t width_axis) { | ||
CHECK(x->shape.size() >= 2) << "Adaptive Pooling input must >= 2-D (H, W)"; |
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Can the input shape be other shape besides 2D and 4D?
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Probably best to assume it's only 4D but I think greater than 4D is supported.
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@KoinFlyp @wweic @yongwww @zhiics @kevinthesun @Laurawly @icemelon9 @yuruofeifei What's the blocking issue for this PR right now? |
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close this pr since inactivity & we would like to go with relay. Feel free to re-open it into upstream tvm directly if needed. |
…generating (apache#5962) * Code migration Start (neo-ai#1) * Init commit: Code migration Start * Add loop_state.cc/h * Add ComputeDAG basic test * Split transform_step out & Update more UTs (neo-ai#3) * Split transform_step out * Update GetProducers & GetConsumers * Update UTs * Add UT for CacheReadWrite & Some bug fix * Add search_task, measure and serialization (neo-ai#4) * Add FollowSplit & FollowFusedSplit tests * Update dag.InferBound & its UT * Add search_task, measure and serialization * Update Serialization UT * Add MetaTileRewritePolicy (neo-ai#5) * Add feature * Add cost_model, meta_tile_rewrite_policy * Add MetaTileRewritePolicy basic UT * Basic Python API for State (neo-ai#6) * Add Basic Python API for State * Add UTs for State * Add Python API: Measure & Task (neo-ai#7) * Update the return value of state operation * Add task * Copy measure.py & utils.py * Fix LocalBuilder * Fix LocalRunner * Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8) * Add basic Python support for ansor.auto_schedule * Update AutoSchedule API * Bug fix for get the attach point of a fused iter * Update UT after infer bug fix * Bug fix & Add python serialization API (neo-ai#10) * Delete C++ UT hack since Python is ready * Add ndarray.non_empty * Update Serialization python API * Improve code style, python wrapper and test cases (neo-ai#11) * Update c++ code style and unit test * Update python State wrapper and test cases * fix unit tests * Add RPCRunner & OpenCL/CUDA test (neo-ai#12) * Add RPCRunner & OpenCL search test * Add CUDA search test * Add RPCRunner test * rebase to upstream/master * Add Ansor basic tutorial (neo-ai#13) * Add basic tutorial * migrate feature extraction (neo-ai#14) * Add XGBModel & RPCRunnerWarpper (neo-ai#15) * Add XGBModel & RPCRunnerWarpper * Revert "Add Parallel Granularity Mutation" * Migrate workload_registry.py (neo-ai#16) * add workload registry * update * update * add task scheduler (neo-ai#17) * Add conv2d cuda tutorial with workload registry (neo-ai#18) * add tune_test.py (the old tune_wkl.py) (neo-ai#19) * add tune_test.py (the old tune_wkl.py) * update * fix measure * fix for gpu * Code refine for tune_test.py & Add a pre load callback (neo-ai#20) * Bug fix for tutorials * Add PreLoadMeasuredStates * Add search_callback support for task tuner * Code refine for tune_test.py * Update * Update * Update * Update * Bug fix * Add python custom sketch rule (neo-ai#21) * Add custom sketch rule * Bug fix * Ansor Relay Integration (without layout rewrite) (neo-ai#22) * relay integration * Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23) * Add single op tune scripts * Add tune subgraph support * Merge all op & all subgraph to one file * Rename file * add explicit_unroll_max_extent (neo-ai#25) * Add Index simplification & API update (neo-ai#26) * Add vectorized cooperative_fetching test * Update math simplify for vectorized CF * File rename * Update tune_network * API update * Update PreLoadMeasuredStates & Some bug fix (neo-ai#27) * Add a threading wrapper to fix the test bug * Set default TVM_USE_AUTO_SCHEDULER to false * Update PreLoadMeasuredStates callback * Add tensorize step for loop_state (neo-ai#31) * Add tensorize step * State python api update (neo-ai#33) * Start to update api * Add compute_dag to state * API update * kernel layout rewrite (neo-ai#28) * kernel layout rewrite * remove some hacks * add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass * set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite * [cache flush] port cache flush to ansor (neo-ai#32) * Improve relay integration (neo-ai#34) * tmp checkpoint * Improve relay integration * Improve relay integration * Fix xgb error & Simplify dispatcher (neo-ai#35) * Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36) * Rename "MetaTileRewritePolicy" to "SketchPolicy". * Add a new class for auto_unroll_max_step, storage_offset in StageNode * fix tune_op_subgraph.py * rebase * Migrate all node::make to noderef's construct function (neo-ai#37) * Start to move xxxnode::make to noderef() * Update * Update * Finish transform_step * Finish comute dag & auto schedule * Update * Update * Update * Update * Update * Code refine * Code refine * Code refine * Update * Update * Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39) * lint fix * clang-format-fix * pylint fix * Update * Recover the double constructor of tvm::PrimExpr * Fix pylint * pylint fix * pylint fix * Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40) * Add MutateComputeLocation and MutateParallel in evolutionary search * fix lint * Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41) * improve loop state python API (stage_tensors -> stage_ops) * fix * ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42) * Bug Fix * Sample example of Custom TensorCore Matmul * Rever Commits, Start to build minimum Ansor system * Code clean for minimum Ansor system * Bug fix & Delete AccessAnalyzer * Delete attachmap & Code clean * Doc update Update statenode::stages from vector to Array * Headfile update & Python doc update * clang-format fix * pylint fix * Update * Doc update * Update * Bug fix after code merge to the new master * clang-format fix * Update * Update * Update std::vector to Array; Update verbosity setting; Some commemts addressed * std::vector->Array & std::string->String * Add init_state to ComputeDAG * Update * Update some unordered_map to Map * clang-format fix * Comments addressed Delete ReplayAndInferBound Delete ReplaySteps & InferBoundCommon * Lint fix * Update * Update * Update * Update * Update * Update * Update * Update * Update * Rename ansor namespace to auto_schedule * Update * Rename ThreadPool to ParallelFor * Add parallel_for * Remove ThreadPool * Update python/tvm/auto_schedule/auto_schedule.py * trigger CI Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com> Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com> Co-authored-by: Zhao Wu <zhaowu@apache.org>
…generating (apache#5962) * Code migration Start (neo-ai#1) * Init commit: Code migration Start * Add loop_state.cc/h * Add ComputeDAG basic test * Split transform_step out & Update more UTs (neo-ai#3) * Split transform_step out * Update GetProducers & GetConsumers * Update UTs * Add UT for CacheReadWrite & Some bug fix * Add search_task, measure and serialization (neo-ai#4) * Add FollowSplit & FollowFusedSplit tests * Update dag.InferBound & its UT * Add search_task, measure and serialization * Update Serialization UT * Add MetaTileRewritePolicy (neo-ai#5) * Add feature * Add cost_model, meta_tile_rewrite_policy * Add MetaTileRewritePolicy basic UT * Basic Python API for State (neo-ai#6) * Add Basic Python API for State * Add UTs for State * Add Python API: Measure & Task (neo-ai#7) * Update the return value of state operation * Add task * Copy measure.py & utils.py * Fix LocalBuilder * Fix LocalRunner * Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8) * Add basic Python support for ansor.auto_schedule * Update AutoSchedule API * Bug fix for get the attach point of a fused iter * Update UT after infer bug fix * Bug fix & Add python serialization API (neo-ai#10) * Delete C++ UT hack since Python is ready * Add ndarray.non_empty * Update Serialization python API * Improve code style, python wrapper and test cases (neo-ai#11) * Update c++ code style and unit test * Update python State wrapper and test cases * fix unit tests * Add RPCRunner & OpenCL/CUDA test (neo-ai#12) * Add RPCRunner & OpenCL search test * Add CUDA search test * Add RPCRunner test * rebase to upstream/master * Add Ansor basic tutorial (neo-ai#13) * Add basic tutorial * migrate feature extraction (neo-ai#14) * Add XGBModel & RPCRunnerWarpper (neo-ai#15) * Add XGBModel & RPCRunnerWarpper * Revert "Add Parallel Granularity Mutation" * Migrate workload_registry.py (neo-ai#16) * add workload registry * update * update * add task scheduler (neo-ai#17) * Add conv2d cuda tutorial with workload registry (neo-ai#18) * add tune_test.py (the old tune_wkl.py) (neo-ai#19) * add tune_test.py (the old tune_wkl.py) * update * fix measure * fix for gpu * Code refine for tune_test.py & Add a pre load callback (neo-ai#20) * Bug fix for tutorials * Add PreLoadMeasuredStates * Add search_callback support for task tuner * Code refine for tune_test.py * Update * Update * Update * Update * Bug fix * Add python custom sketch rule (neo-ai#21) * Add custom sketch rule * Bug fix * Ansor Relay Integration (without layout rewrite) (neo-ai#22) * relay integration * Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23) * Add single op tune scripts * Add tune subgraph support * Merge all op & all subgraph to one file * Rename file * add explicit_unroll_max_extent (neo-ai#25) * Add Index simplification & API update (neo-ai#26) * Add vectorized cooperative_fetching test * Update math simplify for vectorized CF * File rename * Update tune_network * API update * Update PreLoadMeasuredStates & Some bug fix (neo-ai#27) * Add a threading wrapper to fix the test bug * Set default TVM_USE_AUTO_SCHEDULER to false * Update PreLoadMeasuredStates callback * Add tensorize step for loop_state (neo-ai#31) * Add tensorize step * State python api update (neo-ai#33) * Start to update api * Add compute_dag to state * API update * kernel layout rewrite (neo-ai#28) * kernel layout rewrite * remove some hacks * add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass * set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite * [cache flush] port cache flush to ansor (neo-ai#32) * Improve relay integration (neo-ai#34) * tmp checkpoint * Improve relay integration * Improve relay integration * Fix xgb error & Simplify dispatcher (neo-ai#35) * Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36) * Rename "MetaTileRewritePolicy" to "SketchPolicy". * Add a new class for auto_unroll_max_step, storage_offset in StageNode * fix tune_op_subgraph.py * rebase * Migrate all node::make to noderef's construct function (neo-ai#37) * Start to move xxxnode::make to noderef() * Update * Update * Finish transform_step * Finish comute dag & auto schedule * Update * Update * Update * Update * Update * Code refine * Code refine * Code refine * Update * Update * Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39) * lint fix * clang-format-fix * pylint fix * Update * Recover the double constructor of tvm::PrimExpr * Fix pylint * pylint fix * pylint fix * Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40) * Add MutateComputeLocation and MutateParallel in evolutionary search * fix lint * Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41) * improve loop state python API (stage_tensors -> stage_ops) * fix * ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42) * Bug Fix * Sample example of Custom TensorCore Matmul * Rever Commits, Start to build minimum Ansor system * Code clean for minimum Ansor system * Bug fix & Delete AccessAnalyzer * Delete attachmap & Code clean * Doc update Update statenode::stages from vector to Array * Headfile update & Python doc update * clang-format fix * pylint fix * Update * Doc update * Update * Bug fix after code merge to the new master * clang-format fix * Update * Update * Update std::vector to Array; Update verbosity setting; Some commemts addressed * std::vector->Array & std::string->String * Add init_state to ComputeDAG * Update * Update some unordered_map to Map * clang-format fix * Comments addressed Delete ReplayAndInferBound Delete ReplaySteps & InferBoundCommon * Lint fix * Update * Update * Update * Update * Update * Update * Update * Update * Update * Rename ansor namespace to auto_schedule * Update * Rename ThreadPool to ParallelFor * Add parallel_for * Remove ThreadPool * Update python/tvm/auto_schedule/auto_schedule.py * trigger CI Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com> Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com> Co-authored-by: Zhao Wu <zhaowu@apache.org>
…generating (apache#5962) * Code migration Start (neo-ai#1) * Init commit: Code migration Start * Add loop_state.cc/h * Add ComputeDAG basic test * Split transform_step out & Update more UTs (neo-ai#3) * Split transform_step out * Update GetProducers & GetConsumers * Update UTs * Add UT for CacheReadWrite & Some bug fix * Add search_task, measure and serialization (neo-ai#4) * Add FollowSplit & FollowFusedSplit tests * Update dag.InferBound & its UT * Add search_task, measure and serialization * Update Serialization UT * Add MetaTileRewritePolicy (neo-ai#5) * Add feature * Add cost_model, meta_tile_rewrite_policy * Add MetaTileRewritePolicy basic UT * Basic Python API for State (neo-ai#6) * Add Basic Python API for State * Add UTs for State * Add Python API: Measure & Task (neo-ai#7) * Update the return value of state operation * Add task * Copy measure.py & utils.py * Fix LocalBuilder * Fix LocalRunner * Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8) * Add basic Python support for ansor.auto_schedule * Update AutoSchedule API * Bug fix for get the attach point of a fused iter * Update UT after infer bug fix * Bug fix & Add python serialization API (neo-ai#10) * Delete C++ UT hack since Python is ready * Add ndarray.non_empty * Update Serialization python API * Improve code style, python wrapper and test cases (neo-ai#11) * Update c++ code style and unit test * Update python State wrapper and test cases * fix unit tests * Add RPCRunner & OpenCL/CUDA test (neo-ai#12) * Add RPCRunner & OpenCL search test * Add CUDA search test * Add RPCRunner test * rebase to upstream/master * Add Ansor basic tutorial (neo-ai#13) * Add basic tutorial * migrate feature extraction (neo-ai#14) * Add XGBModel & RPCRunnerWarpper (neo-ai#15) * Add XGBModel & RPCRunnerWarpper * Revert "Add Parallel Granularity Mutation" * Migrate workload_registry.py (neo-ai#16) * add workload registry * update * update * add task scheduler (neo-ai#17) * Add conv2d cuda tutorial with workload registry (neo-ai#18) * add tune_test.py (the old tune_wkl.py) (neo-ai#19) * add tune_test.py (the old tune_wkl.py) * update * fix measure * fix for gpu * Code refine for tune_test.py & Add a pre load callback (neo-ai#20) * Bug fix for tutorials * Add PreLoadMeasuredStates * Add search_callback support for task tuner * Code refine for tune_test.py * Update * Update * Update * Update * Bug fix * Add python custom sketch rule (neo-ai#21) * Add custom sketch rule * Bug fix * Ansor Relay Integration (without layout rewrite) (neo-ai#22) * relay integration * Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23) * Add single op tune scripts * Add tune subgraph support * Merge all op & all subgraph to one file * Rename file * add explicit_unroll_max_extent (neo-ai#25) * Add Index simplification & API update (neo-ai#26) * Add vectorized cooperative_fetching test * Update math simplify for vectorized CF * File rename * Update tune_network * API update * Update PreLoadMeasuredStates & Some bug fix (neo-ai#27) * Add a threading wrapper to fix the test bug * Set default TVM_USE_AUTO_SCHEDULER to false * Update PreLoadMeasuredStates callback * Add tensorize step for loop_state (neo-ai#31) * Add tensorize step * State python api update (neo-ai#33) * Start to update api * Add compute_dag to state * API update * kernel layout rewrite (neo-ai#28) * kernel layout rewrite * remove some hacks * add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass * set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite * [cache flush] port cache flush to ansor (neo-ai#32) * Improve relay integration (neo-ai#34) * tmp checkpoint * Improve relay integration * Improve relay integration * Fix xgb error & Simplify dispatcher (neo-ai#35) * Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36) * Rename "MetaTileRewritePolicy" to "SketchPolicy". * Add a new class for auto_unroll_max_step, storage_offset in StageNode * fix tune_op_subgraph.py * rebase * Migrate all node::make to noderef's construct function (neo-ai#37) * Start to move xxxnode::make to noderef() * Update * Update * Finish transform_step * Finish comute dag & auto schedule * Update * Update * Update * Update * Update * Code refine * Code refine * Code refine * Update * Update * Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39) * lint fix * clang-format-fix * pylint fix * Update * Recover the double constructor of tvm::PrimExpr * Fix pylint * pylint fix * pylint fix * Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40) * Add MutateComputeLocation and MutateParallel in evolutionary search * fix lint * Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41) * improve loop state python API (stage_tensors -> stage_ops) * fix * ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42) * Bug Fix * Sample example of Custom TensorCore Matmul * Rever Commits, Start to build minimum Ansor system * Code clean for minimum Ansor system * Bug fix & Delete AccessAnalyzer * Delete attachmap & Code clean * Doc update Update statenode::stages from vector to Array * Headfile update & Python doc update * clang-format fix * pylint fix * Update * Doc update * Update * Bug fix after code merge to the new master * clang-format fix * Update * Update * Update std::vector to Array; Update verbosity setting; Some commemts addressed * std::vector->Array & std::string->String * Add init_state to ComputeDAG * Update * Update some unordered_map to Map * clang-format fix * Comments addressed Delete ReplayAndInferBound Delete ReplaySteps & InferBoundCommon * Lint fix * Update * Update * Update * Update * Update * Update * Update * Update * Update * Rename ansor namespace to auto_schedule * Update * Rename ThreadPool to ParallelFor * Add parallel_for * Remove ThreadPool * Update python/tvm/auto_schedule/auto_schedule.py * trigger CI Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com> Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com> Co-authored-by: Zhao Wu <zhaowu@apache.org>
…generating (apache#5962) * Code migration Start (neo-ai#1) * Init commit: Code migration Start * Add loop_state.cc/h * Add ComputeDAG basic test * Split transform_step out & Update more UTs (neo-ai#3) * Split transform_step out * Update GetProducers & GetConsumers * Update UTs * Add UT for CacheReadWrite & Some bug fix * Add search_task, measure and serialization (neo-ai#4) * Add FollowSplit & FollowFusedSplit tests * Update dag.InferBound & its UT * Add search_task, measure and serialization * Update Serialization UT * Add MetaTileRewritePolicy (neo-ai#5) * Add feature * Add cost_model, meta_tile_rewrite_policy * Add MetaTileRewritePolicy basic UT * Basic Python API for State (neo-ai#6) * Add Basic Python API for State * Add UTs for State * Add Python API: Measure & Task (neo-ai#7) * Update the return value of state operation * Add task * Copy measure.py & utils.py * Fix LocalBuilder * Fix LocalRunner * Add ansor.auto_schedule() API; First AutoSchedule working version(neo-ai#8) * Add basic Python support for ansor.auto_schedule * Update AutoSchedule API * Bug fix for get the attach point of a fused iter * Update UT after infer bug fix * Bug fix & Add python serialization API (neo-ai#10) * Delete C++ UT hack since Python is ready * Add ndarray.non_empty * Update Serialization python API * Improve code style, python wrapper and test cases (neo-ai#11) * Update c++ code style and unit test * Update python State wrapper and test cases * fix unit tests * Add RPCRunner & OpenCL/CUDA test (neo-ai#12) * Add RPCRunner & OpenCL search test * Add CUDA search test * Add RPCRunner test * rebase to upstream/master * Add Ansor basic tutorial (neo-ai#13) * Add basic tutorial * migrate feature extraction (neo-ai#14) * Add XGBModel & RPCRunnerWarpper (neo-ai#15) * Add XGBModel & RPCRunnerWarpper * Revert "Add Parallel Granularity Mutation" * Migrate workload_registry.py (neo-ai#16) * add workload registry * update * update * add task scheduler (neo-ai#17) * Add conv2d cuda tutorial with workload registry (neo-ai#18) * add tune_test.py (the old tune_wkl.py) (neo-ai#19) * add tune_test.py (the old tune_wkl.py) * update * fix measure * fix for gpu * Code refine for tune_test.py & Add a pre load callback (neo-ai#20) * Bug fix for tutorials * Add PreLoadMeasuredStates * Add search_callback support for task tuner * Code refine for tune_test.py * Update * Update * Update * Update * Bug fix * Add python custom sketch rule (neo-ai#21) * Add custom sketch rule * Bug fix * Ansor Relay Integration (without layout rewrite) (neo-ai#22) * relay integration * Add tune_op_subgraph.py & Some code clean for tune_network.py (neo-ai#23) * Add single op tune scripts * Add tune subgraph support * Merge all op & all subgraph to one file * Rename file * add explicit_unroll_max_extent (neo-ai#25) * Add Index simplification & API update (neo-ai#26) * Add vectorized cooperative_fetching test * Update math simplify for vectorized CF * File rename * Update tune_network * API update * Update PreLoadMeasuredStates & Some bug fix (neo-ai#27) * Add a threading wrapper to fix the test bug * Set default TVM_USE_AUTO_SCHEDULER to false * Update PreLoadMeasuredStates callback * Add tensorize step for loop_state (neo-ai#31) * Add tensorize step * State python api update (neo-ai#33) * Start to update api * Add compute_dag to state * API update * kernel layout rewrite (neo-ai#28) * kernel layout rewrite * remove some hacks * add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass * set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite * [cache flush] port cache flush to ansor (neo-ai#32) * Improve relay integration (neo-ai#34) * tmp checkpoint * Improve relay integration * Improve relay integration * Fix xgb error & Simplify dispatcher (neo-ai#35) * Rename "MetaTileRewritePolicy" to "SketchPolicy". (neo-ai#36) * Rename "MetaTileRewritePolicy" to "SketchPolicy". * Add a new class for auto_unroll_max_step, storage_offset in StageNode * fix tune_op_subgraph.py * rebase * Migrate all node::make to noderef's construct function (neo-ai#37) * Start to move xxxnode::make to noderef() * Update * Update * Finish transform_step * Finish comute dag & auto schedule * Update * Update * Update * Update * Update * Code refine * Code refine * Code refine * Update * Update * Some lint fix & Recover the double constructor of tvm::PrimExpr (neo-ai#39) * lint fix * clang-format-fix * pylint fix * Update * Recover the double constructor of tvm::PrimExpr * Fix pylint * pylint fix * pylint fix * Add MutateComputeLocation and MutateParallel in evolutionary search (neo-ai#40) * Add MutateComputeLocation and MutateParallel in evolutionary search * fix lint * Improve loop state python API (stage_tensors -> stage_ops) (neo-ai#41) * improve loop state python API (stage_tensors -> stage_ops) * fix * ComputeDAG bug fix & Add Custom TensorCore Matmul Example (neo-ai#42) * Bug Fix * Sample example of Custom TensorCore Matmul * Rever Commits, Start to build minimum Ansor system * Code clean for minimum Ansor system * Bug fix & Delete AccessAnalyzer * Delete attachmap & Code clean * Doc update Update statenode::stages from vector to Array * Headfile update & Python doc update * clang-format fix * pylint fix * Update * Doc update * Update * Bug fix after code merge to the new master * clang-format fix * Update * Update * Update std::vector to Array; Update verbosity setting; Some commemts addressed * std::vector->Array & std::string->String * Add init_state to ComputeDAG * Update * Update some unordered_map to Map * clang-format fix * Comments addressed Delete ReplayAndInferBound Delete ReplaySteps & InferBoundCommon * Lint fix * Update * Update * Update * Update * Update * Update * Update * Update * Update * Rename ansor namespace to auto_schedule * Update * Rename ThreadPool to ParallelFor * Add parallel_for * Remove ThreadPool * Update python/tvm/auto_schedule/auto_schedule.py * trigger CI Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com> Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com> Co-authored-by: Zhao Wu <zhaowu@apache.org>
…generating (apache#5962) * Code migration Start (#1) * Init commit: Code migration Start * Add loop_state.cc/h * Add ComputeDAG basic test * Split transform_step out & Update more UTs (#3) * Split transform_step out * Update GetProducers & GetConsumers * Update UTs * Add UT for CacheReadWrite & Some bug fix * Add search_task, measure and serialization (#4) * Add FollowSplit & FollowFusedSplit tests * Update dag.InferBound & its UT * Add search_task, measure and serialization * Update Serialization UT * Add MetaTileRewritePolicy (#5) * Add feature * Add cost_model, meta_tile_rewrite_policy * Add MetaTileRewritePolicy basic UT * Basic Python API for State (#6) * Add Basic Python API for State * Add UTs for State * Add Python API: Measure & Task (#7) * Update the return value of state operation * Add task * Copy measure.py & utils.py * Fix LocalBuilder * Fix LocalRunner * Add ansor.auto_schedule() API; First AutoSchedule working version(#8) * Add basic Python support for ansor.auto_schedule * Update AutoSchedule API * Bug fix for get the attach point of a fused iter * Update UT after infer bug fix * Bug fix & Add python serialization API (#10) * Delete C++ UT hack since Python is ready * Add ndarray.non_empty * Update Serialization python API * Improve code style, python wrapper and test cases (#11) * Update c++ code style and unit test * Update python State wrapper and test cases * fix unit tests * Add RPCRunner & OpenCL/CUDA test (#12) * Add RPCRunner & OpenCL search test * Add CUDA search test * Add RPCRunner test * rebase to upstream/master * Add Ansor basic tutorial (#13) * Add basic tutorial * migrate feature extraction (#14) * Add XGBModel & RPCRunnerWarpper (#15) * Add XGBModel & RPCRunnerWarpper * Revert "Add Parallel Granularity Mutation" * Migrate workload_registry.py (#16) * add workload registry * update * update * add task scheduler (#17) * Add conv2d cuda tutorial with workload registry (#18) * add tune_test.py (the old tune_wkl.py) (#19) * add tune_test.py (the old tune_wkl.py) * update * fix measure * fix for gpu * Code refine for tune_test.py & Add a pre load callback (#20) * Bug fix for tutorials * Add PreLoadMeasuredStates * Add search_callback support for task tuner * Code refine for tune_test.py * Update * Update * Update * Update * Bug fix * Add python custom sketch rule (#21) * Add custom sketch rule * Bug fix * Ansor Relay Integration (without layout rewrite) (#22) * relay integration * Add tune_op_subgraph.py & Some code clean for tune_network.py (#23) * Add single op tune scripts * Add tune subgraph support * Merge all op & all subgraph to one file * Rename file * add explicit_unroll_max_extent (#25) * Add Index simplification & API update (#26) * Add vectorized cooperative_fetching test * Update math simplify for vectorized CF * File rename * Update tune_network * API update * Update PreLoadMeasuredStates & Some bug fix (#27) * Add a threading wrapper to fix the test bug * Set default TVM_USE_AUTO_SCHEDULER to false * Update PreLoadMeasuredStates callback * Add tensorize step for loop_state (#31) * Add tensorize step * State python api update (#33) * Start to update api * Add compute_dag to state * API update * kernel layout rewrite (#28) * kernel layout rewrite * remove some hacks * add defuse_ops pass and move kernel_layout_rewrite pass after fuse_ops pass * set TVM_RELAY_DISABLE_BUILD_CACHE for task extraction and prepare_layout_rewrite * [cache flush] port cache flush to ansor (#32) * Improve relay integration (#34) * tmp checkpoint * Improve relay integration * Improve relay integration * Fix xgb error & Simplify dispatcher (#35) * Rename "MetaTileRewritePolicy" to "SketchPolicy". (#36) * Rename "MetaTileRewritePolicy" to "SketchPolicy". * Add a new class for auto_unroll_max_step, storage_offset in StageNode * fix tune_op_subgraph.py * rebase * Migrate all node::make to noderef's construct function (#37) * Start to move xxxnode::make to noderef() * Update * Update * Finish transform_step * Finish comute dag & auto schedule * Update * Update * Update * Update * Update * Code refine * Code refine * Code refine * Update * Update * Some lint fix & Recover the double constructor of tvm::PrimExpr (#39) * lint fix * clang-format-fix * pylint fix * Update * Recover the double constructor of tvm::PrimExpr * Fix pylint * pylint fix * pylint fix * Add MutateComputeLocation and MutateParallel in evolutionary search (#40) * Add MutateComputeLocation and MutateParallel in evolutionary search * fix lint * Improve loop state python API (stage_tensors -> stage_ops) (#41) * improve loop state python API (stage_tensors -> stage_ops) * fix * ComputeDAG bug fix & Add Custom TensorCore Matmul Example (#42) * Bug Fix * Sample example of Custom TensorCore Matmul * Rever Commits, Start to build minimum Ansor system * Code clean for minimum Ansor system * Bug fix & Delete AccessAnalyzer * Delete attachmap & Code clean * Doc update Update statenode::stages from vector to Array * Headfile update & Python doc update * clang-format fix * pylint fix * Update * Doc update * Update * Bug fix after code merge to the new master * clang-format fix * Update * Update * Update std::vector to Array; Update verbosity setting; Some commemts addressed * std::vector->Array & std::string->String * Add init_state to ComputeDAG * Update * Update some unordered_map to Map * clang-format fix * Comments addressed Delete ReplayAndInferBound Delete ReplaySteps & InferBoundCommon * Lint fix * Update * Update * Update * Update * Update * Update * Update * Update * Update * Rename ansor namespace to auto_schedule * Update * Rename ThreadPool to ParallelFor * Add parallel_for * Remove ThreadPool * Update python/tvm/auto_schedule/auto_schedule.py * trigger CI Co-authored-by: Lianmin Zheng <lianminzheng@gmail.com> Co-authored-by: Minmin Sun (孙敏敏) <minmin.smm@alibaba-inc.com> Co-authored-by: Zhao Wu <zhaowu@apache.org>
Consists of an operator map from Prim/ATen operators to NNVM operators and a traversal of PyTorch JIT IR graphs. @wweic @yuruofeifei