IVGCVSW-5721 Remove the Tensorflow Parser from ArmNN
Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ida37d3ee3a1af0c75aa905199bd861726c646846
diff --git a/python/pyarmnn/examples/image_classification/example_utils.py b/python/pyarmnn/examples/image_classification/example_utils.py
index bd43d60..657f9d3 100644
--- a/python/pyarmnn/examples/image_classification/example_utils.py
+++ b/python/pyarmnn/examples/image_classification/example_utils.py
@@ -72,7 +72,7 @@
parser.add_argument("-d", "--data-dir", help="Data directory which contains all the images.",
action="store", default="")
parser.add_argument("-m", "--model-dir",
- help="Model directory which contains the model file (TF, TFLite, ONNX).", action="store",
+ help="Model directory which contains the model file (TFLite, ONNX).", action="store",
default="")
return parser.parse_args()
diff --git a/python/pyarmnn/setup.py b/python/pyarmnn/setup.py
index 9d9f561..7886854 100755
--- a/python/pyarmnn/setup.py
+++ b/python/pyarmnn/setup.py
@@ -284,7 +284,6 @@
add_parsers_ext('OnnxParser', extensions_to_build)
- add_parsers_ext('TfParser', extensions_to_build)
add_parsers_ext('TfLiteParser', extensions_to_build)
add_parsers_ext('Deserializer', extensions_to_build)
diff --git a/python/pyarmnn/src/pyarmnn/__init__.py b/python/pyarmnn/src/pyarmnn/__init__.py
index 410e66b..5cb8bfb 100644
--- a/python/pyarmnn/src/pyarmnn/__init__.py
+++ b/python/pyarmnn/src/pyarmnn/__init__.py
@@ -22,19 +22,6 @@
raise RuntimeError(message)
try:
- from ._generated.pyarmnn_tfparser import ITfParser
-except ImportError as err:
- logger = logging.getLogger(__name__)
- message = "Your ArmNN library instance does not support TF models parser functionality. "
- logger.warning("%s Skipped ITfParser import.", message)
- logger.debug(str(err))
-
-
- def ITfParser():
- """In case people try importing without having Arm NN built with this parser."""
- raise RuntimeError(message)
-
-try:
from ._generated.pyarmnn_tfliteparser import ITfLiteParser, TfLiteParserOptions
except ImportError as err:
logger = logging.getLogger(__name__)
diff --git a/python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i b/python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i
deleted file mode 100644
index 03729ab..0000000
--- a/python/pyarmnn/src/pyarmnn/swig/armnn_tfparser.i
+++ /dev/null
@@ -1,102 +0,0 @@
-//
-// Copyright © 2020 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-%module pyarmnn_tfparser
-%{
-#define SWIG_FILE_WITH_INIT
-#include "armnnTfParser/ITfParser.hpp"
-#include "armnn/INetwork.hpp"
-%}
-
-//typemap definitions and other common stuff
-%include "standard_header.i"
-
-namespace std {
- %template(BindingPointInfo) pair<int, armnn::TensorInfo>;
- %template(MapStringTensorShape) map<std::string, armnn::TensorShape>;
- %template(StringVector) vector<string>;
-}
-
-namespace armnnTfParser
-{
-%feature("docstring",
-"
-Interface for creating a parser object using TensorFlow (https://www.tensorflow.org/) frozen pb files.
-
-Parsers are used to automatically construct Arm NN graphs from model files.
-
-") ITfParser;
-%nodefaultctor ITfParser;
-class ITfParser
-{
-public:
- %feature("docstring",
- "
- Retrieve binding info (layer id and `TensorInfo`) for the network input identified by the given layer name.
-
- Args:
- name (str): Name of the input.
-
- Returns:
- tuple: (`int`, `TensorInfo`).
- ") GetNetworkInputBindingInfo;
- std::pair<int, armnn::TensorInfo> GetNetworkInputBindingInfo(const std::string& name);
-
- %feature("docstring",
- "
- Retrieve binding info (layer id and `TensorInfo`) for the network output identified by the given layer name.
-
- Args:
- name (str): Name of the output.
-
- Returns:
- tuple: (`int`, `TensorInfo`).
- ") GetNetworkOutputBindingInfo;
- std::pair<int, armnn::TensorInfo> GetNetworkOutputBindingInfo(const std::string& name);
-};
-
-%extend ITfParser {
- // This is not a substitution of the default constructor of the Armnn class. It tells swig to create custom __init__
- // method for ITfParser python object that will use static factory method to do the job.
-
- ITfParser() {
- return armnnTfParser::ITfParser::CreateRaw();
- }
-
- // The following does not replace a real destructor of the Armnn class.
- // It creates a functions that will be called when swig object goes out of the scope to clean resources.
- // so the user doesn't need to call ITfParser::Destroy himself.
- // $self` is a pointer to extracted ArmNN ITfParser object.
-
- ~ITfParser() {
- armnnTfParser::ITfParser::Destroy($self);
- }
-
- %feature("docstring",
- "
- Create the network from a pb Protocol buffer file.
-
- Args:
- graphFile (str): Path to the tf model to be parsed.
- inputShapes (dict): A dict containing the input name as a key and `TensorShape` as a value.
- requestedOutputs (list of str): A list of the output tensor names.
-
- Returns:
- INetwork: Parsed network.
-
- Raises:
- RuntimeError: If model file was not found.
- ") CreateNetworkFromBinaryFile;
- %newobject CreateNetworkFromBinaryFile;
- armnn::INetwork* CreateNetworkFromBinaryFile(const char* graphFile,
- const std::map<std::string, armnn::TensorShape>& inputShapes,
- const std::vector<std::string>& requestedOutputs) {
- return $self->CreateNetworkFromBinaryFile(graphFile, inputShapes, requestedOutputs).release();
- }
-
-}
-
-}
-// Clear exception typemap.
-%exception;
diff --git a/python/pyarmnn/swig_generate.py b/python/pyarmnn/swig_generate.py
index a2352c9..e6e2b34 100755
--- a/python/pyarmnn/swig_generate.py
+++ b/python/pyarmnn/swig_generate.py
@@ -108,7 +108,6 @@
wrap_names = ['armnn_version',
'armnn',
'armnn_onnxparser',
- 'armnn_tfparser',
'armnn_tfliteparser',
'armnn_deserializer']
diff --git a/python/pyarmnn/test/test_generated.py b/python/pyarmnn/test/test_generated.py
index f27d565..60d686a 100644
--- a/python/pyarmnn/test/test_generated.py
+++ b/python/pyarmnn/test/test_generated.py
@@ -9,7 +9,6 @@
import pyarmnn._generated.pyarmnn as generated_deserializer
import pyarmnn._generated.pyarmnn_onnxparser as generated_onnx
import pyarmnn._generated.pyarmnn_tfliteparser as generated_tflite
-import pyarmnn._generated.pyarmnn_tfparser as generated_tf
swig_independent_classes = ('IBackend',
'IDeviceSpec',
@@ -28,8 +27,7 @@
inspect.getmembers(generated_armnn, inspect.isclass) +
inspect.getmembers(generated_deserializer, inspect.isclass) +
inspect.getmembers(generated_tflite, inspect.isclass) +
- inspect.getmembers(generated_onnx, inspect.isclass) +
- inspect.getmembers(generated_tf, inspect.isclass)))
+ inspect.getmembers(generated_onnx, inspect.isclass)))
@pytest.mark.parametrize("class_instance", get_classes(swig_independent_classes), ids=lambda x: 'class={}'.format(x[0]))
diff --git a/python/pyarmnn/test/test_tf_parser.py b/python/pyarmnn/test/test_tf_parser.py
deleted file mode 100644
index 796dd71..0000000
--- a/python/pyarmnn/test/test_tf_parser.py
+++ /dev/null
@@ -1,133 +0,0 @@
-# Copyright © 2020 Arm Ltd. All rights reserved.
-# SPDX-License-Identifier: MIT
-import os
-
-import pytest
-import pyarmnn as ann
-import numpy as np
-
-
-@pytest.fixture()
-def parser(shared_data_folder):
- """
- Parse and setup the test network to be used for the tests below
- """
-
- # create tf parser
- parser = ann.ITfParser()
-
- # path to model
- path_to_model = os.path.join(shared_data_folder, 'mock_model.pb')
-
- # tensor shape [1, 28, 28, 1]
- tensorshape = {'input': ann.TensorShape((1, 28, 28, 1))}
-
- # requested_outputs
- requested_outputs = ["output"]
-
- # parse tf binary & create network
- parser.CreateNetworkFromBinaryFile(path_to_model, tensorshape, requested_outputs)
-
- yield parser
-
-
-def test_tf_parser_swig_destroy():
- assert ann.ITfParser.__swig_destroy__, "There is a swig python destructor defined"
- assert ann.ITfParser.__swig_destroy__.__name__ == "delete_ITfParser"
-
-
-def test_check_tf_parser_swig_ownership(parser):
- # Check to see that SWIG has ownership for parser. This instructs SWIG to take
- # ownership of the return value. This allows the value to be automatically
- # garbage-collected when it is no longer in use
- assert parser.thisown
-
-
-def test_tf_parser_get_network_input_binding_info(parser):
- input_binding_info = parser.GetNetworkInputBindingInfo("input")
-
- tensor = input_binding_info[1]
- assert tensor.GetDataType() == 1
- assert tensor.GetNumDimensions() == 4
- assert tensor.GetNumElements() == 28*28*1
- assert tensor.GetQuantizationOffset() == 0
- assert tensor.GetQuantizationScale() == 0
-
-
-def test_tf_parser_get_network_output_binding_info(parser):
- output_binding_info = parser.GetNetworkOutputBindingInfo("output")
-
- tensor = output_binding_info[1]
- assert tensor.GetDataType() == 1
- assert tensor.GetNumDimensions() == 2
- assert tensor.GetNumElements() == 10
- assert tensor.GetQuantizationOffset() == 0
- assert tensor.GetQuantizationScale() == 0
-
-
-def test_tf_filenotfound_exception(shared_data_folder):
- parser = ann.ITfParser()
-
- # path to model
- path_to_model = os.path.join(shared_data_folder, 'some_unknown_model.pb')
-
- # tensor shape [1, 1, 1, 1]
- tensorshape = {'input': ann.TensorShape((1, 1, 1, 1))}
-
- # requested_outputs
- requested_outputs = [""]
-
- # parse tf binary & create network
-
- with pytest.raises(RuntimeError) as err:
- parser.CreateNetworkFromBinaryFile(path_to_model, tensorshape, requested_outputs)
-
- # Only check for part of the exception since the exception returns
- # absolute path which will change on different machines.
- assert 'failed to open' in str(err.value)
-
-
-def test_tf_parser_end_to_end(shared_data_folder):
- parser = ann.ITfParser = ann.ITfParser()
-
- tensorshape = {'input': ann.TensorShape((1, 28, 28, 1))}
- requested_outputs = ["output"]
-
- network = parser.CreateNetworkFromBinaryFile(os.path.join(shared_data_folder, 'mock_model.pb'),
- tensorshape, requested_outputs)
-
- input_binding_info = parser.GetNetworkInputBindingInfo("input")
-
- # load test image data stored in input_tf.npy
- input_tensor_data = np.load(os.path.join(shared_data_folder, 'tf_parser/input_tf.npy')).astype(np.float32)
-
- preferred_backends = [ann.BackendId('CpuAcc'), ann.BackendId('CpuRef')]
-
- options = ann.CreationOptions()
- runtime = ann.IRuntime(options)
-
- opt_network, messages = ann.Optimize(network, preferred_backends, runtime.GetDeviceSpec(), ann.OptimizerOptions())
-
- assert 0 == len(messages)
-
- net_id, messages = runtime.LoadNetwork(opt_network)
-
- assert "" == messages
-
- input_tensors = ann.make_input_tensors([input_binding_info], [input_tensor_data])
-
- outputs_binding_info = []
-
- for output_name in requested_outputs:
- outputs_binding_info.append(parser.GetNetworkOutputBindingInfo(output_name))
-
- output_tensors = ann.make_output_tensors(outputs_binding_info)
-
- runtime.EnqueueWorkload(net_id, input_tensors, output_tensors)
- output_vectors = ann.workload_tensors_to_ndarray(output_tensors)
-
- # Load golden output file for result comparison.
- golden_output = np.load(os.path.join(shared_data_folder, 'tf_parser/golden_output_tf.npy'))
-
- # Check that output matches golden output to 4 decimal places (there are slight rounding differences after this)
- np.testing.assert_almost_equal(output_vectors[0], golden_output, decimal=4)