[llvm] f86d1f9 - Remove ML inlining model artifacts.
Jacob Hegna via llvm-commits
llvm-commits at lists.llvm.org
Mon Jun 21 10:38:22 PDT 2021
Author: Jacob Hegna
Date: 2021-06-21T17:38:09Z
New Revision: f86d1f99b3e9c4819ee0a7b6b785b1ea5feb1627
URL: https://github.com/llvm/llvm-project/commit/f86d1f99b3e9c4819ee0a7b6b785b1ea5feb1627
DIFF: https://github.com/llvm/llvm-project/commit/f86d1f99b3e9c4819ee0a7b6b785b1ea5feb1627.diff
LOG: Remove ML inlining model artifacts.
They are not conducive to being stored in git. Instead, we autogenerate
mock model artifacts for use in tests. Production models can be
specified with the cmake flag LLVM_INLINER_MODEL_PATH.
LLVM_INLINER_MODEL_PATH has two sentinel values:
- download, which will download the most recent compatible model.
- autogenerate, which will autogenerate a "fake" model for testing the
model uptake infrastructure.
Differential Revision: https://reviews.llvm.org/D104251
Added:
llvm/lib/Analysis/models/generate_mock_model.py
llvm/lib/Analysis/models/inlining/config.py
Modified:
llvm/cmake/modules/TensorFlowCompile.cmake
llvm/lib/Analysis/CMakeLists.txt
llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
llvm/test/Transforms/Inline/ML/development-training-log.ll
llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
Removed:
llvm/lib/Analysis/models/inliner/README.txt
llvm/lib/Analysis/models/inliner/output_spec.json
llvm/lib/Analysis/models/inliner/saved_model.pbtxt
llvm/lib/Analysis/models/inliner/variables/variables.data-00000-of-00001
llvm/lib/Analysis/models/inliner/variables/variables.index
################################################################################
diff --git a/llvm/cmake/modules/TensorFlowCompile.cmake b/llvm/cmake/modules/TensorFlowCompile.cmake
index 3454b5f4ed759..27b9d33a33fe5 100644
--- a/llvm/cmake/modules/TensorFlowCompile.cmake
+++ b/llvm/cmake/modules/TensorFlowCompile.cmake
@@ -1,14 +1,45 @@
-# Ensure the ${model} is available at ${final_path}.
-#
-function(tfgetmodel model final_path)
- if (IS_ABSOLUTE ${model})
- set(${final_path} ${model} PARENT_SCOPE)
+function(tf_get_absolute_path path base final_path)
+ if (IS_ABSOLUTE ${path})
+ set(${final_path} ${path} PARENT_SCOPE)
else()
- set(${final_path}
- ${CMAKE_CURRENT_SOURCE_DIR}/${model} PARENT_SCOPE)
+ set(${final_path} ${base}/${path} PARENT_SCOPE)
endif()
endfunction()
+function(tf_get_model model final_path)
+ string(FIND ${model} "http:" pos_http)
+ string(FIND ${model} "https:" pos_https)
+ if (${pos_http} EQUAL 0 OR ${pos_https} EQUAL 0)
+ message("Downloading model " ${model})
+ string(FIND ${model} "/" fname_start REVERSE)
+ math(EXPR fname_start "${fname_start}+1")
+ string(SUBSTRING ${model} ${fname_start}+1 -1 fname)
+ message("Model archive: " ${fname})
+ file(DOWNLOAD ${model} ${CMAKE_CURRENT_BINARY_DIR}/${fname})
+ file(ARCHIVE_EXTRACT INPUT
+ ${CMAKE_CURRENT_BINARY_DIR}/${fname}
+ DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/${fname}_model)
+ set(${final_path} ${CMAKE_CURRENT_BINARY_DIR}/${fname}_model/model PARENT_SCOPE)
+ else()
+ tf_get_absolute_path(${model} ${CMAKE_CURRENT_BINARY_DIR} model_path)
+ set(${final_path} ${model_path} PARENT_SCOPE)
+ endif()
+endfunction()
+
+# Generate a mock model for tests.
+function(generate_mock_model model generate_mock_model_py config)
+ tf_get_absolute_path(${model} ${CMAKE_CURRENT_BINARY_DIR} LLVM_ML_MODELS_ABSOLUTE)
+ tf_get_absolute_path(${generate_mock_model_py} ${CMAKE_CURRENT_SOURCE_DIR} GENERATE_INLINING_MODEL_ABSOLUTE)
+ tf_get_absolute_path(${config} ${CMAKE_CURRENT_SOURCE_DIR} LLVM_ML_MODEL_CONFIG_ABSOLUTE)
+ message(WARNING "Autogenerated mock models should not be used in production builds.")
+ execute_process(COMMAND python3
+ ${GENERATE_INLINING_MODEL_ABSOLUTE}
+ ${LLVM_ML_MODEL_CONFIG_ABSOLUTE}
+ ${LLVM_ML_MODELS_ABSOLUTE}-autogenerated
+ WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}
+ )
+endfunction()
+
# Run the tensorflow compiler (saved_model_cli) on the saved model in the
# ${model} directory, looking for the ${tag_set} tag set, and the SignatureDef
# ${signature_def_key}.
@@ -29,7 +60,7 @@ function(tfcompile model tag_set signature_def_key fname cpp_class)
${hdr_file} " and object " ${obj_file}
" files for model " ${model})
else()
- tfgetmodel(${model} LLVM_ML_MODELS_ABSOLUTE)
+ tf_get_absolute_path(${model} ${CMAKE_CURRENT_BINARY_DIR} LLVM_ML_MODELS_ABSOLUTE)
message("Using model at " ${LLVM_ML_MODELS_ABSOLUTE})
add_custom_command(OUTPUT ${obj_file} ${hdr_file}
COMMAND ${TENSORFLOW_AOT_COMPILER} aot_compile_cpu
@@ -52,5 +83,32 @@ function(tfcompile model tag_set signature_def_key fname cpp_class)
set(GENERATED_HEADERS ${GENERATED_HEADERS} ${hdr_file} PARENT_SCOPE)
set_source_files_properties(${hdr_file} PROPERTIES
GENERATED 1)
-
+
+endfunction()
+
+function(tf_find_and_compile model default_url default_path generation_config tag_set signature_def_key fname cpp_class)
+ if ("${model}" STREQUAL "download")
+ set(model ${default_url})
+ endif()
+
+ if ("${model}" STREQUAL "autogenerate")
+ generate_mock_model(${default_path} models/generate_mock_model.py ${generation_config})
+ set(model ${default_path}-autogenerated)
+ endif()
+
+ tf_get_model(${model} LLVM_ML_MODELS_ABSOLUTE)
+ tfcompile(${LLVM_ML_MODELS_ABSOLUTE} ${tag_set} ${signature_def_key} ${fname} ${cpp_class})
+
+ set(GENERATED_OBJS ${GENERATED_OBJS} ${obj_file} PARENT_SCOPE)
+ set_source_files_properties(${obj_file} PROPERTIES
+ GENERATED 1 EXTERNAL_OBJECT 1)
+
+ set(GENERATED_HEADERS ${GENERATED_HEADERS} ${hdr_file} PARENT_SCOPE)
+ set_source_files_properties(${hdr_file} PROPERTIES
+ GENERATED 1)
+
+ set(GeneratedMLSources ${GeneratedMLSources} ${GENERATED_HEADERS} PARENT_SCOPE)
+ set(MLDeps ${MLDeps} tf_xla_runtime PARENT_SCOPE)
+ set(MLLinkDeps ${MLLinkDeps} tf_xla_runtime ${GENERATED_OBJS} PARENT_SCOPE)
+
endfunction()
diff --git a/llvm/lib/Analysis/CMakeLists.txt b/llvm/lib/Analysis/CMakeLists.txt
index 559947ca23ef5..0165e4bc1bcc0 100644
--- a/llvm/lib/Analysis/CMakeLists.txt
+++ b/llvm/lib/Analysis/CMakeLists.txt
@@ -1,19 +1,33 @@
if (DEFINED LLVM_HAVE_TF_AOT OR DEFINED LLVM_HAVE_TF_API)
+ include(TensorFlowCompile)
+ set(LLVM_INLINER_MODEL_PATH_DEFAULT "models/inliner-Oz")
+
+ # This url points to the most recent most which is known to be compatible with
+ # LLVM. When better models are published, this url should be updated to aid
+ # discoverability.
+ set(LLVM_INLINER_MODEL_CURRENT_URL "https://github.com/google/ml-compiler-opt/releases/download/inlining-Oz-v0.1/inlining-Oz-acabaf6-v0.1.tar.gz")
+
if (DEFINED LLVM_HAVE_TF_AOT)
- set(LLVM_INLINER_MODEL_PATH "models/inliner"
- CACHE STRING
- "ML-driven inliner policy location (path to saved model)")
- include(TensorFlowCompile)
- tfcompile(${LLVM_INLINER_MODEL_PATH} serve action InlinerSizeModel llvm::InlinerSizeModel)
- list(APPEND GeneratedMLSources
- ${GENERATED_HEADERS}
+ # If the path is empty, autogenerate the model
+ if (NOT DEFINED LLVM_INLINER_MODEL_PATH OR "${LLVM_INLINER_MODEL_PATH}" STREQUAL "")
+ set(LLVM_INLINER_MODEL_PATH "autogenerate")
+ message(WARNING "LLVM_INLINER_MODEL_PATH was not set: autogenerating a model to finish the build.")
+ endif()
+
+ tf_find_and_compile(
+ ${LLVM_INLINER_MODEL_PATH}
+ ${LLVM_INLINER_MODEL_CURRENT_URL}
+ ${LLVM_INLINER_MODEL_PATH_DEFAULT}
+ "models/inlining/config.py"
+ serve
+ action
+ InlinerSizeModel
+ llvm::InlinerSizeModel
)
- LIST(APPEND MLDeps tf_xla_runtime)
- LIST(APPEND MLLinkDeps tf_xla_runtime ${GENERATED_OBJS})
endif()
if (DEFINED LLVM_HAVE_TF_API)
- LIST(APPEND MLLinkDeps ${tensorflow_c_api})
+ list(APPEND MLLinkDeps ${tensorflow_c_api})
endif()
endif()
diff --git a/llvm/lib/Analysis/models/generate_mock_model.py b/llvm/lib/Analysis/models/generate_mock_model.py
new file mode 100644
index 0000000000000..f1170abba3836
--- /dev/null
+++ b/llvm/lib/Analysis/models/generate_mock_model.py
@@ -0,0 +1,69 @@
+"""Generate a mock model for LLVM tests.
+
+The generated model is not a neural net - it is just a tf.function with the
+correct input and output parameters. By construction, the mock model will always
+output 1.
+"""
+
+import os
+import importlib.util
+import sys
+
+import tensorflow as tf
+
+
+def get_output_spec_path(path):
+ return os.path.join(path, 'output_spec.json')
+
+
+def build_mock_model(path, signature):
+ """Build and save the mock model with the given signature"""
+ module = tf.Module()
+
+ # We have to set this useless variable in order for the TF C API to correctly
+ # intake it
+ module.var = tf.Variable(0.)
+
+ def action(*inputs):
+ s = tf.reduce_sum([tf.cast(x, tf.float32) for x in tf.nest.flatten(inputs)])
+ return {signature['output']: float('inf') + s + module.var}
+
+ module.action = tf.function()(action)
+ action = {'action': module.action.get_concrete_function(signature['inputs'])}
+ tf.saved_model.save(module, path, signatures=action)
+
+ output_spec_path = get_output_spec_path(path)
+ with open(output_spec_path, 'w') as f:
+ print(f'Writing output spec to {output_spec_path}.')
+ f.write(signature['output_spec'])
+
+
+def get_external_signature(config_path):
+ """Get the signature for the desired model.
+
+ We manually import the python file at config_path to avoid adding a gin
+ dependency to the LLVM build.
+ """
+ spec = importlib.util.spec_from_file_location('config', config_path)
+ config = importlib.util.module_from_spec(spec)
+ spec.loader.exec_module(config)
+
+ return {
+ 'inputs': config.get_input_signature(),
+ 'output': config.get_output_signature(),
+ 'output_spec': config.get_output_spec()
+ }
+
+
+def main(argv):
+ assert len(argv) == 3
+ config_path = argv[1]
+ model_path = argv[2]
+
+ print(f'Using config file at [{argv[1]}]')
+ signature = get_external_signature(config_path)
+ build_mock_model(model_path, signature)
+
+
+if __name__ == '__main__':
+ main(sys.argv)
diff --git a/llvm/lib/Analysis/models/inliner/README.txt b/llvm/lib/Analysis/models/inliner/README.txt
deleted file mode 100644
index a76bb8930d6e1..0000000000000
--- a/llvm/lib/Analysis/models/inliner/README.txt
+++ /dev/null
@@ -1,3 +0,0 @@
-Reference model for inliner -Oz decision policy.
-Note that, currently, this model is also referenced by test/Transforms/Inline/ML
-tests - if replacing it, check those tests, too.
diff --git a/llvm/lib/Analysis/models/inliner/output_spec.json b/llvm/lib/Analysis/models/inliner/output_spec.json
deleted file mode 100644
index 5f9d13d8f8b85..0000000000000
--- a/llvm/lib/Analysis/models/inliner/output_spec.json
+++ /dev/null
@@ -1,14 +0,0 @@
-[
- {
- "logging_name": "inlining_decision",
- "tensor_spec": {
- "name": "StatefulPartitionedCall",
- "port": 0,
- "type": "int64_t",
- "shape": [
- 1
- ]
- }
- }
-]
-
\ No newline at end of file
diff --git a/llvm/lib/Analysis/models/inliner/saved_model.pbtxt b/llvm/lib/Analysis/models/inliner/saved_model.pbtxt
deleted file mode 100644
index ec522a8b7c353..0000000000000
--- a/llvm/lib/Analysis/models/inliner/saved_model.pbtxt
+++ /dev/null
@@ -1,32634 +0,0 @@
-saved_model_schema_version: 1
-meta_graphs {
- meta_info_def {
- stripped_op_list {
- op {
- name: "Const"
- output_arg {
- name: "output"
- type_attr: "dtype"
- }
- attr {
- name: "value"
- type: "tensor"
- }
- attr {
- name: "dtype"
- type: "type"
- }
- }
- op {
- name: "NoOp"
- }
- op {
- name: "PartitionedCall"
- input_arg {
- name: "args"
- type_list_attr: "Tin"
- }
- output_arg {
- name: "output"
- type_list_attr: "Tout"
- }
- attr {
- name: "Tin"
- type: "list(type)"
- has_minimum: true
- }
- attr {
- name: "Tout"
- type: "list(type)"
- has_minimum: true
- }
- attr {
- name: "f"
- type: "func"
- }
- attr {
- name: "config"
- type: "string"
- default_value {
- s: ""
- }
- }
- attr {
- name: "config_proto"
- type: "string"
- default_value {
- s: ""
- }
- }
- attr {
- name: "executor_type"
- type: "string"
- default_value {
- s: ""
- }
- }
- }
- op {
- name: "Placeholder"
- output_arg {
- name: "output"
- type_attr: "dtype"
- }
- attr {
- name: "dtype"
- type: "type"
- }
- attr {
- name: "shape"
- type: "shape"
- default_value {
- shape {
- unknown_rank: true
- }
- }
- }
- }
- op {
- name: "ReadVariableOp"
- input_arg {
- name: "resource"
- type: DT_RESOURCE
- }
- output_arg {
- name: "value"
- type_attr: "dtype"
- }
- attr {
- name: "dtype"
- type: "type"
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- is_stateful: true
- }
- op {
- name: "StatefulPartitionedCall"
- input_arg {
- name: "args"
- type_list_attr: "Tin"
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- output_arg {
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- attr {
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- attr {
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- default_value {
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- op {
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- name: "container"
- type: "string"
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- type: "string"
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- attr {
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- type: "type"
- }
- attr {
- name: "shape"
- type: "shape"
- }
- attr {
- name: "allowed_devices"
- type: "list(string)"
- default_value {
- list {
- }
- }
- }
- is_stateful: true
- }
- }
- tags: "serve"
- tensorflow_version: "1.15.0"
- tensorflow_git_version: "unknown"
- stripped_default_attrs: true
- }
- graph_def {
- node {
- name: "train_step"
- op: "VarHandleOp"
- attr {
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- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- values {
- key: "state"
- value {
- tuple_value {
- }
- }
- }
- values {
- key: "info"
- value {
- tuple_value {
- }
- }
- }
- }
- }
- }
- }
- concrete_functions {
- key: "__inference_polymorphic_action_fn_946"
- value {
- bound_inputs: 10
- bound_inputs: 11
- bound_inputs: 12
- bound_inputs: 13
- bound_inputs: 14
- bound_inputs: 15
- canonicalized_input_signature {
- tuple_value {
- values {
- tuple_value {
- values {
- named_tuple_value {
- name: "TimeStep"
- values {
- key: "step_type"
- value {
- tensor_spec_value {
- name: "step_type"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT32
- }
- }
- }
- values {
- key: "reward"
- value {
- tensor_spec_value {
- name: "reward"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_FLOAT
- }
- }
- }
- values {
- key: "discount"
- value {
- tensor_spec_value {
- name: "discount"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_FLOAT
- }
- }
- }
- values {
- key: "observation"
- value {
- dict_value {
- fields {
- key: "callee_basic_block_count"
- value {
- tensor_spec_value {
- name: "callee_basic_block_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "callee_conditionally_executed_blocks"
- value {
- tensor_spec_value {
- name: "callee_conditionally_executed_blocks"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "callee_users"
- value {
- tensor_spec_value {
- name: "callee_users"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "caller_basic_block_count"
- value {
- tensor_spec_value {
- name: "caller_basic_block_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "caller_conditionally_executed_blocks"
- value {
- tensor_spec_value {
- name: "caller_conditionally_executed_blocks"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "caller_users"
- value {
- tensor_spec_value {
- name: "caller_users"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "callsite_height"
- value {
- tensor_spec_value {
- name: "callsite_height"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "cost_estimate"
- value {
- tensor_spec_value {
- name: "cost_estimate"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "edge_count"
- value {
- tensor_spec_value {
- name: "edge_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "inlining_default"
- value {
- tensor_spec_value {
- name: "inlining_default"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "node_count"
- value {
- tensor_spec_value {
- name: "node_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "nr_ctant_params"
- value {
- tensor_spec_value {
- name: "nr_ctant_params"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- }
- }
- }
- }
- }
- values {
- tuple_value {
- }
- }
- }
- }
- values {
- dict_value {
- }
- }
- }
- }
- output_signature {
- named_tuple_value {
- name: "PolicyStep"
- values {
- key: "action"
- value {
- tensor_spec_value {
- name: "action"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- values {
- key: "state"
- value {
- tuple_value {
- }
- }
- }
- values {
- key: "info"
- value {
- tuple_value {
- }
- }
- }
- }
- }
- }
- }
- concrete_functions {
- key: "__inference_signature_wrapper_4619026"
- value {
- bound_inputs: 10
- bound_inputs: 11
- bound_inputs: 12
- bound_inputs: 13
- bound_inputs: 14
- bound_inputs: 15
- canonicalized_input_signature {
- tuple_value {
- values {
- tuple_value {
- }
- }
- values {
- dict_value {
- fields {
- key: "callee_basic_block_count"
- value {
- tensor_spec_value {
- name: "callee_basic_block_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "callee_conditionally_executed_blocks"
- value {
- tensor_spec_value {
- name: "callee_conditionally_executed_blocks"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "callee_users"
- value {
- tensor_spec_value {
- name: "callee_users"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "caller_basic_block_count"
- value {
- tensor_spec_value {
- name: "caller_basic_block_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "caller_conditionally_executed_blocks"
- value {
- tensor_spec_value {
- name: "caller_conditionally_executed_blocks"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "caller_users"
- value {
- tensor_spec_value {
- name: "caller_users"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "callsite_height"
- value {
- tensor_spec_value {
- name: "callsite_height"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "cost_estimate"
- value {
- tensor_spec_value {
- name: "cost_estimate"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "discount"
- value {
- tensor_spec_value {
- name: "discount"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_FLOAT
- }
- }
- }
- fields {
- key: "edge_count"
- value {
- tensor_spec_value {
- name: "edge_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "inlining_default"
- value {
- tensor_spec_value {
- name: "inlining_default"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "node_count"
- value {
- tensor_spec_value {
- name: "node_count"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "nr_ctant_params"
- value {
- tensor_spec_value {
- name: "nr_ctant_params"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- fields {
- key: "reward"
- value {
- tensor_spec_value {
- name: "reward"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_FLOAT
- }
- }
- }
- fields {
- key: "step_type"
- value {
- tensor_spec_value {
- name: "step_type"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT32
- }
- }
- }
- }
- }
- }
- }
- output_signature {
- dict_value {
- fields {
- key: "inlining_decision"
- value {
- tensor_spec_value {
- name: "inlining_decision"
- shape {
- dim {
- size: 1
- }
- }
- dtype: DT_INT64
- }
- }
- }
- }
- }
- }
- }
- concrete_functions {
- key: "__inference_signature_wrapper_4619033"
- value {
- canonicalized_input_signature {
- tuple_value {
- values {
- tuple_value {
- }
- }
- values {
- dict_value {
- }
- }
- }
- }
- output_signature {
- dict_value {
- }
- }
- }
- }
- concrete_functions {
- key: "__inference_signature_wrapper_4619048"
- value {
- bound_inputs: 4
- canonicalized_input_signature {
- tuple_value {
- values {
- tuple_value {
- }
- }
- values {
- dict_value {
- }
- }
- }
- }
- output_signature {
- dict_value {
- fields {
- key: "int64"
- value {
- tensor_spec_value {
- name: "int64"
- shape {
- }
- dtype: DT_INT64
- }
- }
- }
- }
- }
- }
- }
- }
-}
-
diff --git a/llvm/lib/Analysis/models/inliner/variables/variables.data-00000-of-00001 b/llvm/lib/Analysis/models/inliner/variables/variables.data-00000-of-00001
deleted file mode 100644
index ee7d7060867e7..0000000000000
Binary files a/llvm/lib/Analysis/models/inliner/variables/variables.data-00000-of-00001 and /dev/null
diff er
diff --git a/llvm/lib/Analysis/models/inliner/variables/variables.index b/llvm/lib/Analysis/models/inliner/variables/variables.index
deleted file mode 100644
index 7e0c10c1780e0..0000000000000
Binary files a/llvm/lib/Analysis/models/inliner/variables/variables.index and /dev/null
diff er
diff --git a/llvm/lib/Analysis/models/inlining/config.py b/llvm/lib/Analysis/models/inlining/config.py
new file mode 100644
index 0000000000000..3da64a6973975
--- /dev/null
+++ b/llvm/lib/Analysis/models/inlining/config.py
@@ -0,0 +1,56 @@
+"""Inlining Training config."""
+
+import tensorflow as tf
+
+POLICY_DECISION_LABEL = 'inlining_decision'
+POLICY_OUTPUT_SPEC = """
+[
+ {
+ "logging_name": "inlining_decision",
+ "tensor_spec": {
+ "name": "StatefulPartitionedCall",
+ "port": 0,
+ "type": "int64_t",
+ "shape": [
+ 1
+ ]
+ }
+ }
+]
+"""
+
+
+# pylint: disable=g-complex-comprehension
+def get_input_signature():
+ """Returns the list of features for LLVM inlining."""
+ # int64 features
+ inputs = [
+ tf.TensorSpec(dtype=tf.int64, shape=(), name=key) for key in [
+ 'caller_basic_block_count', 'caller_conditionally_executed_blocks',
+ 'caller_users', 'callee_basic_block_count',
+ 'callee_conditionally_executed_blocks', 'callee_users',
+ 'nr_ctant_params', 'node_count', 'edge_count', 'callsite_height',
+ 'cost_estimate', 'inlining_default'
+ ]
+ ]
+
+ # float32 features
+ inputs.extend([
+ tf.TensorSpec(dtype=tf.float32, shape=(), name=key)
+ for key in ['discount', 'reward']
+ ])
+
+ # int32 features
+ inputs.extend([
+ tf.TensorSpec(dtype=tf.int32, shape=(), name=key)
+ for key in ['step_type']
+ ])
+ return inputs
+
+
+def get_output_signature():
+ return POLICY_DECISION_LABEL
+
+
+def get_output_spec():
+ return POLICY_OUTPUT_SPEC
diff --git a/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll b/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
index abcc27e86e6dd..aa01f5ef94c29 100644
--- a/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
+++ b/llvm/test/Transforms/Inline/ML/bounds-checks-rewards.ll
@@ -6,19 +6,23 @@
; factor, we penalize the 'bad' decision.
; REQUIRES: have_tf_api
;
+; Generate mock model
+; RUN: rm -rf %t && mkdir %t
+; RUN: python3 %S/../../../../lib/Analysis/models/generate_mock_model.py %S/../../../../lib/Analysis/models/inlining/config.py %t
+;
; When the bounds are very wide ("no bounds"), all inlinings happen.
-; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -training-log=- -enable-ml-inliner=development -ml-advisor-size-increase-threshold=10.0 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=NOBOUNDS
+; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=- -enable-ml-inliner=development -ml-advisor-size-increase-threshold=10.0 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=NOBOUNDS
;
; When the bounds are very restrictive, the first inlining happens but it's
; considered as "bad" (since it trips over the bounds) and its reward is a
; penalty. However, the mandatory inlining, which is considered next, happens.
; No other inlinings happend.
-; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -training-log=- -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.0 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=BOUNDS
+; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=- -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.0 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=BOUNDS
;
; With more restrictive bounds, the first inlining happens and is OK. The
; mandatory inlining happens next, and it trips over the bounds, which then
; forces no further inlinings.
-; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -training-log=- -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.1 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=RELAXED-BOUNDS
+; RUN: opt -passes=scc-oz-module-inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-model-under-training=%t -training-log=- -enable-ml-inliner=development -ml-advisor-size-increase-threshold=1.1 -S < %s 2>&1 | FileCheck %s --check-prefix=CHECK --check-prefix=RELAXED-BOUNDS
target datalayout = "e-m:e-p270:32:32-p271:32:32-p272:64:64-i64:64-f80:128-n8:16:32:64-S128"
target triple = "x86_64-grtev4-linux-gnu"
@@ -61,4 +65,4 @@ attributes #0 = { alwaysinline }
; it won't be inlined.
; NOBOUNDS-NOT: @may_not_be_inlined
; RELAXED-BOUNDS: call i64 @may_not_be_inlined
-; BOUNDS: call i64 @may_not_be_inlined
\ No newline at end of file
+; BOUNDS: call i64 @may_not_be_inlined
diff --git a/llvm/test/Transforms/Inline/ML/development-training-log.ll b/llvm/test/Transforms/Inline/ML/development-training-log.ll
index 0dcff29a343d5..6b6e5994a7057 100644
--- a/llvm/test/Transforms/Inline/ML/development-training-log.ll
+++ b/llvm/test/Transforms/Inline/ML/development-training-log.ll
@@ -1,9 +1,13 @@
; Test that we can produce a log if we have or do not have a model, in development mode.
; REQUIRES: have_tf_api
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-output-spec-override=%S/Inputs/test_output_spec.json -S < %s | FileCheck %s --check-prefixes=EXTRA-OUTPUTS,CHECK
+; Generate mock model
+; RUN: rm -rf %t && mkdir %t
+; RUN: python3 %S/../../../../lib/Analysis/models/generate_mock_model.py %S/../../../../lib/Analysis/models/inlining/config.py %t
+;
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%t -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%t -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -ml-inliner-output-spec-override=%S/Inputs/test_output_spec.json -S < %s | FileCheck %s --check-prefixes=EXTRA-OUTPUTS,CHECK
; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-ir2native-model=%S/../../../../unittests/Analysis/Inputs/ir2native_x86_64_model -S < %s | FileCheck %s
-; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -S < %s | FileCheck %s --check-prefix=NOREWARD
+; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -ml-inliner-model-under-training=%t -S < %s | FileCheck %s --check-prefix=NOREWARD
; RUN: opt -enable-ml-inliner=development -passes=scc-oz-module-inliner -training-log=- -S < %s | FileCheck %s --check-prefix=NOREWARD
target datalayout = "e-m:e-i64:64-f80:128-n8:16:32:64-S128"
@@ -44,7 +48,7 @@ define dso_local i32 @top() {
; Check we produce a protobuf that has inlining decisions and rewards.
; CHECK-NOT: fake_extra_output
; EXTRA-OUTPUTS: key: "fake_extra_output" value: {
-; EXTRA-OUTPUTS-NEXT: feature: { int64_list: { value: [1] } }
+; EXTRA-OUTPUTS-NEXT: feature: { int64_list: { value: [{{[0-9]+}}] } }
; CHECK: key: "inlining_decision" value: {
; CHECK-NEXT: feature: { int64_list: { value: [1] } }
; CHECK: key: "delta_size" value: {
diff --git a/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll b/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
index 0546c9a23d4e2..0b3e40c083767 100644
--- a/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
+++ b/llvm/test/Transforms/Inline/ML/ml-test-development-mode.ll
@@ -6,5 +6,7 @@
; for the 'release' mode.
;
; REQUIRES: have_tf_api
+; RUN: rm -rf %t && mkdir %t
+; RUN: python3 %S/../../../../lib/Analysis/models/generate_mock_model.py %S/../../../../lib/Analysis/models/inlining/config.py %t
; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=default -S < %S/Inputs/test-module.ll 2>&1 | FileCheck %S/Inputs/test-module.ll --check-prefix=DEFAULT
-; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=development -ml-inliner-model-under-training=%S/../../../../lib/Analysis/models/inliner -S < %S/Inputs/test-module.ll 2>&1 | FileCheck %S/Inputs/test-module.ll --check-prefix=CHECK
+; RUN: opt -passes=scc-oz-module-inliner -enable-ml-inliner=development -ml-inliner-model-under-training=%t -S < %S/Inputs/test-module.ll 2>&1 | FileCheck %S/Inputs/test-module.ll --check-prefix=CHECK
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