Fix a couple of issues with the python package tools (#10858)

* Tweaks to the model utils
  * Add handling for a dim_value of -1 when replacing the entire input shape. This occurs in models exported from PaddlePaddle
  * make pytorch helpers accessible in package
  * make QDQ helpers accessible in package

cmake/onnxruntime_python.cmake

@@ -398,6 +398,9 @@ file(GLOB onnxruntime_mobile_helpers_srcs CONFIGURE_DEPENDS
     ${REPO_ROOT}/tools/ci_build/github/android/nnapi_supported_ops.md
     ${REPO_ROOT}/tools/ci_build/github/apple/coreml_supported_ops.md
 )
+file(GLOB onnxruntime_qdq_helper_srcs CONFIGURE_DEPENDS
+    ${REPO_ROOT}/tools/python/util/qdq_helpers/*.py
+)
 
 set(build_output_target onnxruntime_common)
 if(NOT onnxruntime_ENABLE_STATIC_ANALYSIS)
@@ -409,6 +412,7 @@ add_custom_command(
   COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/datasets
   COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools
   COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/mobile_helpers
+  COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/qdq_helpers
   COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/ort_format_model
   COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/ort_format_model/ort_flatbuffers_py
   COMMAND ${CMAKE_COMMAND} -E make_directory $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/transformers
@@ -461,7 +465,17 @@ add_custom_command(
   COMMAND ${CMAKE_COMMAND} -E copy
       ${onnxruntime_mobile_util_srcs}
       $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/
-      COMMAND ${CMAKE_COMMAND} -E copy
+  # append the /tools/python/utils imports to the __init__.py that came from /onnxruntime/tools.
+  # we're aggregating scripts from two different locations, and only include selected functionality from
+  # /tools/python/util. due to that we take the full __init__.py from /onnxruntime/tools and append
+  # the required content from /tools/python/util/__init__append.py.
+  COMMAND ${CMAKE_COMMAND} -E cat
+      ${REPO_ROOT}/tools/python/util/__init__append.py >>
+      $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/__init__.py
+  COMMAND ${CMAKE_COMMAND} -E copy
+      ${onnxruntime_qdq_helper_srcs}
+      $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/qdq_helpers/
+  COMMAND ${CMAKE_COMMAND} -E copy
       ${onnxruntime_mobile_helpers_srcs}
       $<TARGET_FILE_DIR:${build_output_target}>/onnxruntime/tools/mobile_helpers/
   COMMAND ${CMAKE_COMMAND} -E copy

tools/python/util/__init__.py

@@ -4,8 +4,6 @@
 from .get_azcopy import get_azcopy
 from .logger import get_logger
 from .platform_helpers import (is_windows, is_macOS, is_linux)
-# Test what is needed here to use in a script
-# from .pytorch_export_helpers import infer_input_info
 from .run import run
 
 try:
@@ -13,3 +11,9 @@ try:
     from .reduced_build_config_parser import parse_config
 except ImportError:
     get_logger('tools_python_utils').info('flatbuffers module is not installed. parse_config will not be available')
+
+# see if we can make the pytorch helpers available.
+import importlib.util  # noqa
+have_torch = importlib.util.find_spec("torch")
+if have_torch:
+    from .pytorch_export_helpers import infer_input_info

tools/python/util/__init__append.py

@@ -0,0 +1,5 @@
+# appended to the __init__.py in the onnxruntime module's 'tools' folder from /tools/python/util/__init__append.py
+import importlib.util
+have_torch = importlib.util.find_spec("torch")
+if have_torch:
+    from .pytorch_export_helpers import infer_input_info  # noqa

tools/python/util/onnx_model_utils.py

@@ -124,6 +124,34 @@ def _replace_symbolic_dim_value(graph: onnx.GraphProto, **kwargs):
     update_dim_values(graph.value_info)
 
 
+def _remove_invalid_dim_values_impl(graph: onnx.GraphProto):
+    def clear_invalid_values(value):
+        if value.type.HasField("tensor_type"):
+            shape = value.type.tensor_type.shape
+            if shape:
+                for dim in shape.dim:
+                    if dim.HasField('dim_value') and dim.dim_value < 1:
+                        dim.Clear()
+
+    for i in graph.input:
+        clear_invalid_values(i)
+
+    for o in graph.output:
+        clear_invalid_values(o)
+
+    for vi in graph.value_info:
+        clear_invalid_values(vi)
+
+
+def remove_invalid_dim_values(graph: onnx.GraphProto):
+    '''
+    Iterate the graph and subgraphs, unsetting any dim_value entries that have a value of less than 1.
+    These are typically erroneously inserted by a converter to represent a dynamic dimension.
+    :param graph: GraphProto to update
+    '''
+    iterate_graph_per_graph_func(graph, _remove_invalid_dim_values_impl)
+
+
 def make_dim_param_fixed(graph: onnx.GraphProto, param_name: str, value: int):
     '''
     Iterate all values in the graph, replacing dim_param in a tensor shape with the provided value.
@@ -144,6 +172,9 @@ def make_input_shape_fixed(graph: onnx.GraphProto, input_name: str, fixed_shape:
     :param fixed_shape: Shape to use.
     '''
 
+    # remove any invalid dim values first. typically this is a dim_value of -1.
+    remove_invalid_dim_values(graph)
+
     for i in graph.input:
         if i.name == input_name:
             if not i.type.HasField("tensor_type"):