Add experiments flag to converter

tfjs-converter/python/requirements-exp.txt

@@ -0,0 +1,8 @@
+h5py>=2.8.0
+numpy>=1.16.4,<1.19.0
+six>=1.12.0
+tf-nightly-cpu>=2.4.0.dev20200806,<3
+tensorflow-hub==0.7.0
+PyInquirer==1.0.3
+pylint==1.9.4; python_version < '3.0'
+pylint==2.5.0; python_version > '3.0'

tfjs-converter/python/run-python-tests.sh

@@ -16,6 +16,12 @@
 
 # A script that runs all Python unit tests in tfjs-layers.
 
+function print_usage() {
+  echo "Usage:"
+  echo "  run-python-tests.sh <requirments_file>"
+  echo
+}
+
 set -e
 
 SCRIPTS_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
@@ -28,8 +34,26 @@ TMP_VENV_DIR="$(mktemp -u).venv"
 virtualenv -p "python" "${TMP_VENV_DIR}"
 source "${TMP_VENV_DIR}/bin/activate"
 
-pip install -r "${SCRIPTS_DIR}/requirements-dev.txt"
+# There is one argument (requirements_file), please update this constant when
+# you adding more arguments.
+ARGS_COUNT=1
+
+# Default requirements file name.
+REQ_FILE="${SCRIPTS_DIR}/requirements-dev.txt"
+
+# Show the usage message if there are too many arguments.
+if [[ $# > ARGS_COUNT ]]; then
+  print_usage
+  exit 1
+fi
+
+# Use the user specified requirements file name.
+if [[ $# == 1 ]]; then
+  REQ_FILE=$1
+fi
+pip install -r "${REQ_FILE}"
 
+# Run pylint for tensorflowjs directory
 cd "${SCRIPTS_DIR}"
 pylint --rcfile=.pylintrc tensorflowjs
 
@@ -45,5 +69,6 @@ echo
 echo "All tests passed."
 echo
 
+# Clean up
 deactivate
 rm -rf "${TMP_VENV_DIR}"

tfjs-converter/python/tensorflowjs/converters/BUILD

@@ -159,6 +159,7 @@ py_library(
         "//tensorflowjs:expect_numpy_installed",
         "//tensorflowjs:expect_tensorflow_hub_installed",
         "//tensorflowjs:expect_tensorflow_installed",
+        "//tensorflowjs:expect_graph_transforms_installed",
         "//tensorflowjs:resource_loader",
         "//tensorflowjs:version",
         "//tensorflowjs:write_weights",

tfjs-converter/python/tensorflowjs/converters/common.py

@@ -59,6 +59,7 @@
 STRIP_DEBUG_OPS = 'strip_debug_ops'
 WEIGHT_SHARD_SIZE_BYTES = 'weight_shard_size_bytes'
 CONTROL_FLOW_V2 = 'control_flow_v2'
+EXPERIMENTS = 'experiments'
 
 def get_converted_by():
   """Get the convertedBy string for storage in model artifacts."""

tfjs-converter/python/tensorflowjs/converters/converter.py

@@ -105,7 +105,8 @@ def dispatch_keras_h5_to_tfjs_graph_model_conversion(
     skip_op_check=False,
     strip_debug_ops=False,
     weight_shard_size_bytes=1024 * 1024 * 4,
-    control_flow_v2=False):
+    control_flow_v2=False,
+    experiments=False):
   """
   Convert a keras HDF5-format model to tfjs GraphModel artifacts.
 
@@ -120,6 +121,8 @@ def dispatch_keras_h5_to_tfjs_graph_model_conversion(
     strip_debug_ops: Bool whether to allow unsupported debug ops.
     weight_shard_size_bytes: Shard size (in bytes) of the weight files.
       The size of each weight file will be <= this value.
+    control_flow_v2: Bool whether to enable control flow v2 ops.
+    experiments: Bool enable experimental features.
   """
 
   if not os.path.exists(h5_path):
@@ -143,7 +146,8 @@ def dispatch_keras_h5_to_tfjs_graph_model_conversion(
       skip_op_check=skip_op_check,
       strip_debug_ops=strip_debug_ops,
       weight_shard_size_bytes=weight_shard_size_bytes,
-      control_flow_v2=control_flow_v2)
+      control_flow_v2=control_flow_v2,
+      experiments=experiments)
 
   # Clean up the temporary SavedModel directory.
   shutil.rmtree(temp_savedmodel_dir)
@@ -331,7 +335,9 @@ def dispatch_tfjs_layers_model_to_tfjs_graph_conversion(
     quantization_dtype_map=None,
     skip_op_check=False,
     strip_debug_ops=False,
-    weight_shard_size_bytes=1024 * 1024 * 4):
+    weight_shard_size_bytes=1024 * 1024 * 4,
+    control_flow_v2=False,
+    experiments=False):
   """Converts a TensorFlow.js Layers Model to TensorFlow.js Graph Model.
 
   This conversion often benefits speed of inference, due to the graph
@@ -348,7 +354,8 @@ def dispatch_tfjs_layers_model_to_tfjs_graph_conversion(
     strip_debug_ops: Bool whether to allow unsupported debug ops.
     weight_shard_size_bytes: Shard size (in bytes) of the weight files.
       The size of each weight file will be <= this value.
-
+    control_flow_v2: Bool whether to enable control flow v2 ops.
+    experiments: Bool enable experimental features.
   Raises:
     ValueError, if `config_json_path` is not a path to a valid JSON
       file, or if h5_path points to an existing directory.
@@ -382,7 +389,9 @@ def dispatch_tfjs_layers_model_to_tfjs_graph_conversion(
       quantization_dtype_map=quantization_dtype_map,
       skip_op_check=skip_op_check,
       strip_debug_ops=strip_debug_ops,
-      weight_shard_size_bytes=weight_shard_size_bytes)
+      weight_shard_size_bytes=weight_shard_size_bytes,
+      control_flow_v2=control_flow_v2,
+      experiments=experiments)
 
   # Clean up temporary HDF5 file.
   os.remove(temp_h5_path)
@@ -575,9 +584,16 @@ def get_arg_parser():
       '"tf_frozen_model".')
   parser.add_argument(
       '--%s' % common.CONTROL_FLOW_V2,
-      type=str,
+      type=bool,
+      default=False,
       help='Enable control flow v2 ops, this would improve inference '
       'performance on models with branches or loops.')
+  parser.add_argument(
+      '--%s' % common.EXPERIMENTS,
+      type=bool,
+      default=False,
+      help='Enable experimental features, you should only enable this flag '
+      'when using Python3 and TensorFlow nightly build.')
   return parser
 
 def convert(arguments):
@@ -660,7 +676,8 @@ def convert(arguments):
         skip_op_check=args.skip_op_check,
         strip_debug_ops=args.strip_debug_ops,
         weight_shard_size_bytes=weight_shard_size_bytes,
-        control_flow_v2=args.control_flow_v2)
+        control_flow_v2=args.control_flow_v2,
+        experiments=args.experiments)
   elif (input_format == common.KERAS_SAVED_MODEL and
         output_format == common.TFJS_LAYERS_MODEL):
     dispatch_keras_saved_model_to_tensorflowjs_conversion(
@@ -678,7 +695,8 @@ def convert(arguments):
         skip_op_check=args.skip_op_check,
         strip_debug_ops=args.strip_debug_ops,
         weight_shard_size_bytes=weight_shard_size_bytes,
-        control_flow_v2=args.control_flow_v2)
+        control_flow_v2=args.control_flow_v2,
+        experiments=args.experiments)
   elif (input_format == common.TF_HUB_MODEL and
         output_format == common.TFJS_GRAPH_MODEL):
     tf_saved_model_conversion_v2.convert_tf_hub_module(
@@ -689,7 +707,8 @@ def convert(arguments):
         skip_op_check=args.skip_op_check,
         strip_debug_ops=args.strip_debug_ops,
         weight_shard_size_bytes=weight_shard_size_bytes,
-        control_flow_v2=args.control_flow_v2)
+        control_flow_v2=args.control_flow_v2,
+        experiments=args.experiments)
   elif (input_format == common.TFJS_LAYERS_MODEL and
         output_format == common.KERAS_MODEL):
     dispatch_tensorflowjs_to_keras_h5_conversion(args.input_path,
@@ -711,15 +730,18 @@ def convert(arguments):
         quantization_dtype_map=quantization_dtype_map,
         skip_op_check=args.skip_op_check,
         strip_debug_ops=args.strip_debug_ops,
-        weight_shard_size_bytes=weight_shard_size_bytes)
+        weight_shard_size_bytes=weight_shard_size_bytes,
+        control_flow_v2=args.control_flow_v2,
+        experiments=args.experiments)
   elif (input_format == common.TF_FROZEN_MODEL and
         output_format == common.TFJS_GRAPH_MODEL):
     tf_saved_model_conversion_v2.convert_tf_frozen_model(
         args.input_path, args.output_node_names, args.output_path,
         quantization_dtype_map=quantization_dtype_map,
         skip_op_check=args.skip_op_check,
         strip_debug_ops=args.strip_debug_ops,
-        weight_shard_size_bytes=weight_shard_size_bytes)
+        weight_shard_size_bytes=weight_shard_size_bytes,
+        experiments=args.experiments)
   else:
     raise ValueError(
         'Unsupported input_format - output_format pair: %s - %s' %