Merge pull request #19 from NodLabs/ean-export-modules

Add shark-runner command line options for saving modules.

shark/iree_utils.py

@@ -15,6 +15,8 @@
 import iree.runtime as ireert
 import iree.compiler as ireec
 import numpy as np
+import os
+from shark.torch_mlir_utils import get_module_name_for_asm_dump
 
 IREE_DEVICE_MAP = {"cpu": "dylib", "gpu": "cuda", "vulkan": "vulkan"}
 
@@ -32,6 +34,14 @@ def get_iree_compiled_module(module, device: str):
     ModuleCompiled = ctx.modules.module["forward"]
     return ModuleCompiled, config
 
+def export_iree_module_to_vmfb(module, device: str, directory: str):
+    module_name = get_module_name_for_asm_dump(module)
+    flatbuffer_blob = ireec.compile_str(
+        str(module), target_backends=[IREE_DEVICE_MAP[device]]
+    )
+    filename = os.path.join(directory, module_name + ".vmfb")
+    with open(filename, 'wb') as f:
+        f.write(flatbuffer_blob)
 
 def get_results(compiled_vm, input, config):
     """TODO: Documentation"""

shark/shark_runner.py

@@ -12,11 +12,18 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from shark.torch_mlir_utils import get_torch_mlir_module
-from shark.iree_utils import get_results, get_iree_compiled_module
+from shark.torch_mlir_utils import get_torch_mlir_module, export_module_to_mlir_file
+from shark.iree_utils import get_results, get_iree_compiled_module, export_iree_module_to_vmfb
+import argparse
+import os
 # from functorch_utils import AOTModule
 
-
+def dir_path(path):
+    if os.path.isdir(path):
+        return path
+    else:
+        raise argparse.ArgumentTypeError(f"readable_dir:{path} is not a valid path")
+              
 class SharkRunner:
     """TODO: Write the description"""
 
@@ -29,16 +36,25 @@ class SharkRunner:
         tracing_required: bool,
         from_aot: bool,
     ):
+        self.parser = argparse.ArgumentParser(description='SHARK runner.')
+        self.parser.add_argument("--repro_dir", help="Directory to which module files will be saved for reproduction or debugging.", type=dir_path, default="/tmp/")
+        self.parser.add_argument("--save_mlir", default=False, action="store_true", help="Saves input MLIR module to /tmp/ directory.")
+        self.parser.add_argument("--save_vmfb", default=False, action="store_true", help="Saves iree .vmfb module to /tmp/ directory.")
+        self.parser.parse_args(namespace=self)
         self.torch_module = model
         self.input = input
         self.torch_mlir_module = get_torch_mlir_module(
             model, input, dynamic, tracing_required, from_aot
         )
+        if self.save_mlir:
+            export_module_to_mlir_file(self.torch_mlir_module, self.repro_dir)
+        if self.save_vmfb:
+            export_iree_module_to_vmfb(self.torch_mlir_module, device, self.repro_dir)
         (
             self.iree_compilation_module,
             self.iree_config,
         ) = get_iree_compiled_module(self.torch_mlir_module, device)
-
+        
     def forward(self, input):
         return get_results(
             self.iree_compilation_module, input, self.iree_config

shark/torch_mlir_utils.py

@@ -15,7 +15,10 @@
 import torch
 import io
 import pickle
+import sys
+import os
 
+from io import StringIO
 from torch_mlir.dialects.torch.importer.jit_ir import (
     ClassAnnotator,
     ModuleBuilder,
@@ -28,7 +31,23 @@ from torch_mlir_e2e_test.torchscript.serialization import (
 
 from torch_mlir.passmanager import PassManager
 from torch_mlir_e2e_test.torchscript.annotations import annotate_args, export
+from torch_mlir.ir import StringAttr
 
+def get_module_name_for_asm_dump(module):
+    """Gets a name suitable for an assembly dump.
+    The name is not guaranteed to be unique.
+    """
+    if not "torch.debug_module_name" in module.operation.attributes:
+        return "UnnammedModule"
+    return StringAttr(module.operation.attributes["torch.debug_module_name"]).value
+    
+def export_module_to_mlir_file(module, directory: str):
+    """Writes MLIR module to /tmp/module.mlir for debugging or performance use."""
+    module_name = get_module_name_for_asm_dump(module)
+    asm = module.operation.get_asm()
+    filename = os.path.join(directory, module_name + ".mlir")
+    with open(filename, 'w') as f:
+        f.write(asm)
 
 def get_input_annotations(inputs: tuple, dynamic: bool) -> list:
     """TODO: Include necessary documentation"""