IVGCVSW-5721 Remove the Tensorflow Parser from ArmNN

Signed-off-by: Nikhil Raj <nikhil.raj@arm.com>
Change-Id: Ida37d3ee3a1af0c75aa905199bd861726c646846

7 files changed, 2 insertions, 254 deletions

diff --git a/python/pyarmnn/examples/image_classification/example_utils.py b/python/pyarmnn/examples/image_classification/example_utils.py
index bd43d60da5..657f9d3559 100644
--- a/python/pyarmnn/examples/image_classification/example_utils.py
+++ b/python/pyarmnn/examples/image_classification/example_utils.py
@@ -72,7 +72,7 @@ def parse_command_line(desc: str = ""):
     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 9d9f561ef9..78868549f3 100755
--- a/python/pyarmnn/setup.py
+++ b/python/pyarmnn/setup.py
@@ -284,7 +284,6 @@ if __name__ == '__main__':
 
 
     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 410e66be11..5cb8bfb6cd 100644
--- a/python/pyarmnn/src/pyarmnn/__init__.py
+++ b/python/pyarmnn/src/pyarmnn/__init__.py
@@ -22,19 +22,6 @@ except ImportError as err:
         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 03729abbf8..0000000000
--- 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 a2352c9063..e6e2b346be 100755
--- a/python/pyarmnn/swig_generate.py
+++ b/python/pyarmnn/swig_generate.py
@@ -108,7 +108,6 @@ if __name__ == "__main__":
     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 f27d565c2b..60d686afcb 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_armnn
 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 @@ def get_classes(swig_independent_classes: Tuple):
                        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 796dd71e7b..0000000000
--- 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)