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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2021/05/04 15:07:05 UTC
[GitHub] [tvm] vegaluisjose opened a new pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
vegaluisjose opened a new pull request #7972:
URL: https://github.com/apache/tvm/pull/7972
The following PR adds support to test end-to-end(sw/hw) MobileNet using the Verilator backend. This is build upon this [commit](https://github.com/apache/tvm-vta/commit/dfe9f572a43d41e0c1ecdf036cea97042a0febfe).
@tmoreau89
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[GitHub] [tvm] tmoreau89 merged pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 merged pull request #7972:
URL: https://github.com/apache/tvm/pull/7972
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[GitHub] [tvm] vegaluisjose commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
vegaluisjose commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-841865508
It takes about the same time as running the pure software version.
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[GitHub] [tvm] tmoreau89 commented on a change in pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 commented on a change in pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#discussion_r633131636
##########
File path: tests/python/contrib/test_verilator/test_mobilenet.py
##########
@@ -0,0 +1,240 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import tvm
+from tvm import te, relay, transform
+from tvm.contrib.download import download_testdata
+from tvm.contrib import graph_executor as runtime
+
+import os
+from PIL import Image
+import numpy as np
+
+from test_verilator.infrastructure import (
+ compile_hardware,
+ compiler_opts,
+ offload,
+ clear_stats,
+ stats,
+)
+
+
+def extract(path):
+ """Extract a tgz or gz file.
+
+ Paramters
+ ---------
+ path : Str
+ The path of the compressed file.
+ """
+ import tarfile
+
+ if path.endswith("tgz") or path.endswith("gz"):
+ dir_path = os.path.dirname(path)
+ tar = tarfile.open(path)
+ tar.extractall(path=dir_path)
+ tar.close()
+ else:
+ raise RuntimeError("Could not decompress the file: " + path)
+
+
+def get_real_image(im_height, im_width):
+ """Get a real image.
+
+ Paramters
+ ---------
+ im_height : Int
+ The image height.
+
+ im_width : Int
+ The image width.
+
+ Returns
+ -------
+ data: Data
+ The image array.
+ """
+ repo_base = "https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV1/"
+ img_name = "elephant-299.jpg"
+ image_url = os.path.join(repo_base, img_name)
+ img_path = download_testdata(image_url, img_name, module="data")
+ image = Image.open(img_path).resize((im_height, im_width))
+ x = np.array(image).astype("uint8")
+ data = np.reshape(x, (1, im_height, im_width, 3))
+ return data
+
+
+def get_mobilenet_model():
+ """Return mobilenet model."""
+ model_url = "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz"
+ model_path = download_testdata(
+ model_url, "mobilenet_v1_1.0_224_quant.tgz", module=["tf", "official"]
+ )
+ model_dir = os.path.dirname(model_path)
+ extract(model_path)
+ tflite_model_file = os.path.join(model_dir, "mobilenet_v1_1.0_224_quant.tflite")
+ tflite_model_buf = open(tflite_model_file, "rb").read()
+ try:
+ import tflite
+
+ return tflite.Model.GetRootAsModel(tflite_model_buf, 0)
+ except AttributeError:
+ import tflite.Model
+
+ return tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+
+
+def get_input_tensor_name():
+ """Return input name."""
+ return "input"
+
+
+def compile_model_to_relay(model):
+ """Compile model to relay.
+
+ Paramters
+ ---------
+ model : Model
+ The input model.
+
+ Returns
+ -------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+ """
+ input_tensor = get_input_tensor_name()
+ input_shape = (1, 224, 224, 3)
+ input_dtype = "uint8"
+ mod, params = relay.frontend.from_tflite(
+ model,
+ shape_dict={input_tensor: input_shape},
+ dtype_dict={input_tensor: input_dtype},
+ )
+ return mod, params
+
+
+def run_model(mod, params=None, opts=None):
+ """Run model.
+
+ Paramters
+ ---------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+
+ opts: Dict
+ The compiler options.
+
+ Returns
+ -------
+ out: Data
+ The output data.
+ """
+ with transform.PassContext(opt_level=3, config={"relay.ext.verilator.options": opts}):
+ lib = relay.build(mod, target="llvm", params=params)
+ module = runtime.GraphModule(lib["default"](tvm.cpu()))
+ image_data = get_real_image(224, 224)
+ input_tensor = get_input_tensor_name()
+ module.set_input(input_tensor, image_data)
+ module.run()
+ out = module.get_output(0).asnumpy()
+ return out
+
+
+def get_labels():
+ """Return labels."""
+ label_file_url = "".join(
+ [
+ "https://raw.githubusercontent.com/",
+ "tensorflow/tensorflow/master/tensorflow/lite/java/demo/",
+ "app/src/main/assets/",
+ "labels_mobilenet_quant_v1_224.txt",
+ ]
+ )
+ label_file = "labels_mobilenet_quant_v1_224.txt"
+ label_path = download_testdata(label_file_url, label_file, module="data")
+ # List of 1001 classes
+ with open(label_path) as f:
+ labels = f.readlines()
+ return labels
+
+
+def check_result(res):
+ """Check prediction against labels."""
+ labels = get_labels()
+ predictions = np.squeeze(res)
+ prediction = np.argmax(predictions)
+ # 387 is the elephant
+ tvm.testing.assert_allclose(prediction, 387, rtol=1e-5, atol=1e-5)
Review comment:
In this case can't we just assert that prediction is equal to 387?
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[GitHub] [tvm] tqchen commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tqchen commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-839728345
Thanks @vegaluisjose . just want to make sure that the mobile net simulation won't cost a long time to finish. otherwise it would be still good to have unit test models that can finish in a reasonable amount of time. We can move mobile net tests to nightly category later once we support nightlies
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[GitHub] [tvm] vegaluisjose commented on a change in pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
vegaluisjose commented on a change in pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#discussion_r633691488
##########
File path: tests/python/contrib/test_verilator/test_mobilenet.py
##########
@@ -0,0 +1,240 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import tvm
+from tvm import te, relay, transform
+from tvm.contrib.download import download_testdata
+from tvm.contrib import graph_executor as runtime
+
+import os
+from PIL import Image
+import numpy as np
+
+from test_verilator.infrastructure import (
+ compile_hardware,
+ compiler_opts,
+ offload,
+ clear_stats,
+ stats,
+)
+
+
+def extract(path):
+ """Extract a tgz or gz file.
+
+ Paramters
+ ---------
+ path : Str
+ The path of the compressed file.
+ """
+ import tarfile
+
+ if path.endswith("tgz") or path.endswith("gz"):
+ dir_path = os.path.dirname(path)
+ tar = tarfile.open(path)
+ tar.extractall(path=dir_path)
+ tar.close()
+ else:
+ raise RuntimeError("Could not decompress the file: " + path)
+
+
+def get_real_image(im_height, im_width):
+ """Get a real image.
+
+ Paramters
+ ---------
+ im_height : Int
+ The image height.
+
+ im_width : Int
+ The image width.
+
+ Returns
+ -------
+ data: Data
+ The image array.
+ """
+ repo_base = "https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV1/"
+ img_name = "elephant-299.jpg"
+ image_url = os.path.join(repo_base, img_name)
+ img_path = download_testdata(image_url, img_name, module="data")
+ image = Image.open(img_path).resize((im_height, im_width))
+ x = np.array(image).astype("uint8")
+ data = np.reshape(x, (1, im_height, im_width, 3))
+ return data
+
+
+def get_mobilenet_model():
+ """Return mobilenet model."""
+ model_url = "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz"
+ model_path = download_testdata(
+ model_url, "mobilenet_v1_1.0_224_quant.tgz", module=["tf", "official"]
+ )
+ model_dir = os.path.dirname(model_path)
+ extract(model_path)
+ tflite_model_file = os.path.join(model_dir, "mobilenet_v1_1.0_224_quant.tflite")
+ tflite_model_buf = open(tflite_model_file, "rb").read()
+ try:
+ import tflite
+
+ return tflite.Model.GetRootAsModel(tflite_model_buf, 0)
+ except AttributeError:
+ import tflite.Model
+
+ return tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+
+
+def get_input_tensor_name():
+ """Return input name."""
+ return "input"
+
+
+def compile_model_to_relay(model):
+ """Compile model to relay.
+
+ Paramters
+ ---------
+ model : Model
+ The input model.
+
+ Returns
+ -------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+ """
+ input_tensor = get_input_tensor_name()
+ input_shape = (1, 224, 224, 3)
+ input_dtype = "uint8"
+ mod, params = relay.frontend.from_tflite(
+ model,
+ shape_dict={input_tensor: input_shape},
+ dtype_dict={input_tensor: input_dtype},
+ )
+ return mod, params
+
+
+def run_model(mod, params=None, opts=None):
+ """Run model.
+
+ Paramters
+ ---------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+
+ opts: Dict
+ The compiler options.
+
+ Returns
+ -------
+ out: Data
+ The output data.
+ """
+ with transform.PassContext(opt_level=3, config={"relay.ext.verilator.options": opts}):
+ lib = relay.build(mod, target="llvm", params=params)
+ module = runtime.GraphModule(lib["default"](tvm.cpu()))
+ image_data = get_real_image(224, 224)
+ input_tensor = get_input_tensor_name()
+ module.set_input(input_tensor, image_data)
+ module.run()
+ out = module.get_output(0).asnumpy()
+ return out
+
+
+def get_labels():
+ """Return labels."""
+ label_file_url = "".join(
+ [
+ "https://raw.githubusercontent.com/",
+ "tensorflow/tensorflow/master/tensorflow/lite/java/demo/",
+ "app/src/main/assets/",
+ "labels_mobilenet_quant_v1_224.txt",
+ ]
+ )
+ label_file = "labels_mobilenet_quant_v1_224.txt"
+ label_path = download_testdata(label_file_url, label_file, module="data")
+ # List of 1001 classes
+ with open(label_path) as f:
+ labels = f.readlines()
+ return labels
+
+
+def check_result(res):
+ """Check prediction against labels."""
+ labels = get_labels()
+ predictions = np.squeeze(res)
+ prediction = np.argmax(predictions)
+ # 387 is the elephant
+ tvm.testing.assert_allclose(prediction, 387, rtol=1e-5, atol=1e-5)
Review comment:
Fixed
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[GitHub] [tvm] tmoreau89 commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-841868436
I tested the two tests on my local machine, `test_mobilenet.py` and `test_verilator_ops.py`; total runtime is 22.06s. @tqchen I'm going to approve the PR, but let us know if you think that is too long. IMO that is a reasonable runtime.
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[GitHub] [tvm] vegaluisjose commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
vegaluisjose commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-841865508
It takes about the same time as running the pure software version.
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[GitHub] [tvm] tmoreau89 commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-841864898
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[GitHub] [tvm] tmoreau89 commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-843366847
Thank you @vegaluisjose the PR has been merged.
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[GitHub] [tvm] vegaluisjose commented on a change in pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
vegaluisjose commented on a change in pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#discussion_r633691488
##########
File path: tests/python/contrib/test_verilator/test_mobilenet.py
##########
@@ -0,0 +1,240 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import tvm
+from tvm import te, relay, transform
+from tvm.contrib.download import download_testdata
+from tvm.contrib import graph_executor as runtime
+
+import os
+from PIL import Image
+import numpy as np
+
+from test_verilator.infrastructure import (
+ compile_hardware,
+ compiler_opts,
+ offload,
+ clear_stats,
+ stats,
+)
+
+
+def extract(path):
+ """Extract a tgz or gz file.
+
+ Paramters
+ ---------
+ path : Str
+ The path of the compressed file.
+ """
+ import tarfile
+
+ if path.endswith("tgz") or path.endswith("gz"):
+ dir_path = os.path.dirname(path)
+ tar = tarfile.open(path)
+ tar.extractall(path=dir_path)
+ tar.close()
+ else:
+ raise RuntimeError("Could not decompress the file: " + path)
+
+
+def get_real_image(im_height, im_width):
+ """Get a real image.
+
+ Paramters
+ ---------
+ im_height : Int
+ The image height.
+
+ im_width : Int
+ The image width.
+
+ Returns
+ -------
+ data: Data
+ The image array.
+ """
+ repo_base = "https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV1/"
+ img_name = "elephant-299.jpg"
+ image_url = os.path.join(repo_base, img_name)
+ img_path = download_testdata(image_url, img_name, module="data")
+ image = Image.open(img_path).resize((im_height, im_width))
+ x = np.array(image).astype("uint8")
+ data = np.reshape(x, (1, im_height, im_width, 3))
+ return data
+
+
+def get_mobilenet_model():
+ """Return mobilenet model."""
+ model_url = "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz"
+ model_path = download_testdata(
+ model_url, "mobilenet_v1_1.0_224_quant.tgz", module=["tf", "official"]
+ )
+ model_dir = os.path.dirname(model_path)
+ extract(model_path)
+ tflite_model_file = os.path.join(model_dir, "mobilenet_v1_1.0_224_quant.tflite")
+ tflite_model_buf = open(tflite_model_file, "rb").read()
+ try:
+ import tflite
+
+ return tflite.Model.GetRootAsModel(tflite_model_buf, 0)
+ except AttributeError:
+ import tflite.Model
+
+ return tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+
+
+def get_input_tensor_name():
+ """Return input name."""
+ return "input"
+
+
+def compile_model_to_relay(model):
+ """Compile model to relay.
+
+ Paramters
+ ---------
+ model : Model
+ The input model.
+
+ Returns
+ -------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+ """
+ input_tensor = get_input_tensor_name()
+ input_shape = (1, 224, 224, 3)
+ input_dtype = "uint8"
+ mod, params = relay.frontend.from_tflite(
+ model,
+ shape_dict={input_tensor: input_shape},
+ dtype_dict={input_tensor: input_dtype},
+ )
+ return mod, params
+
+
+def run_model(mod, params=None, opts=None):
+ """Run model.
+
+ Paramters
+ ---------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+
+ opts: Dict
+ The compiler options.
+
+ Returns
+ -------
+ out: Data
+ The output data.
+ """
+ with transform.PassContext(opt_level=3, config={"relay.ext.verilator.options": opts}):
+ lib = relay.build(mod, target="llvm", params=params)
+ module = runtime.GraphModule(lib["default"](tvm.cpu()))
+ image_data = get_real_image(224, 224)
+ input_tensor = get_input_tensor_name()
+ module.set_input(input_tensor, image_data)
+ module.run()
+ out = module.get_output(0).asnumpy()
+ return out
+
+
+def get_labels():
+ """Return labels."""
+ label_file_url = "".join(
+ [
+ "https://raw.githubusercontent.com/",
+ "tensorflow/tensorflow/master/tensorflow/lite/java/demo/",
+ "app/src/main/assets/",
+ "labels_mobilenet_quant_v1_224.txt",
+ ]
+ )
+ label_file = "labels_mobilenet_quant_v1_224.txt"
+ label_path = download_testdata(label_file_url, label_file, module="data")
+ # List of 1001 classes
+ with open(label_path) as f:
+ labels = f.readlines()
+ return labels
+
+
+def check_result(res):
+ """Check prediction against labels."""
+ labels = get_labels()
+ predictions = np.squeeze(res)
+ prediction = np.argmax(predictions)
+ # 387 is the elephant
+ tvm.testing.assert_allclose(prediction, 387, rtol=1e-5, atol=1e-5)
Review comment:
Fixed
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[GitHub] [tvm] tmoreau89 commented on a change in pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 commented on a change in pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#discussion_r633131636
##########
File path: tests/python/contrib/test_verilator/test_mobilenet.py
##########
@@ -0,0 +1,240 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+import tvm
+from tvm import te, relay, transform
+from tvm.contrib.download import download_testdata
+from tvm.contrib import graph_executor as runtime
+
+import os
+from PIL import Image
+import numpy as np
+
+from test_verilator.infrastructure import (
+ compile_hardware,
+ compiler_opts,
+ offload,
+ clear_stats,
+ stats,
+)
+
+
+def extract(path):
+ """Extract a tgz or gz file.
+
+ Paramters
+ ---------
+ path : Str
+ The path of the compressed file.
+ """
+ import tarfile
+
+ if path.endswith("tgz") or path.endswith("gz"):
+ dir_path = os.path.dirname(path)
+ tar = tarfile.open(path)
+ tar.extractall(path=dir_path)
+ tar.close()
+ else:
+ raise RuntimeError("Could not decompress the file: " + path)
+
+
+def get_real_image(im_height, im_width):
+ """Get a real image.
+
+ Paramters
+ ---------
+ im_height : Int
+ The image height.
+
+ im_width : Int
+ The image width.
+
+ Returns
+ -------
+ data: Data
+ The image array.
+ """
+ repo_base = "https://github.com/dmlc/web-data/raw/master/tensorflow/models/InceptionV1/"
+ img_name = "elephant-299.jpg"
+ image_url = os.path.join(repo_base, img_name)
+ img_path = download_testdata(image_url, img_name, module="data")
+ image = Image.open(img_path).resize((im_height, im_width))
+ x = np.array(image).astype("uint8")
+ data = np.reshape(x, (1, im_height, im_width, 3))
+ return data
+
+
+def get_mobilenet_model():
+ """Return mobilenet model."""
+ model_url = "https://storage.googleapis.com/download.tensorflow.org/models/mobilenet_v1_2018_08_02/mobilenet_v1_1.0_224_quant.tgz"
+ model_path = download_testdata(
+ model_url, "mobilenet_v1_1.0_224_quant.tgz", module=["tf", "official"]
+ )
+ model_dir = os.path.dirname(model_path)
+ extract(model_path)
+ tflite_model_file = os.path.join(model_dir, "mobilenet_v1_1.0_224_quant.tflite")
+ tflite_model_buf = open(tflite_model_file, "rb").read()
+ try:
+ import tflite
+
+ return tflite.Model.GetRootAsModel(tflite_model_buf, 0)
+ except AttributeError:
+ import tflite.Model
+
+ return tflite.Model.Model.GetRootAsModel(tflite_model_buf, 0)
+
+
+def get_input_tensor_name():
+ """Return input name."""
+ return "input"
+
+
+def compile_model_to_relay(model):
+ """Compile model to relay.
+
+ Paramters
+ ---------
+ model : Model
+ The input model.
+
+ Returns
+ -------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+ """
+ input_tensor = get_input_tensor_name()
+ input_shape = (1, 224, 224, 3)
+ input_dtype = "uint8"
+ mod, params = relay.frontend.from_tflite(
+ model,
+ shape_dict={input_tensor: input_shape},
+ dtype_dict={input_tensor: input_dtype},
+ )
+ return mod, params
+
+
+def run_model(mod, params=None, opts=None):
+ """Run model.
+
+ Paramters
+ ---------
+ mod: Module
+ The relay module.
+
+ params: Parameters
+ The model parameters.
+
+ opts: Dict
+ The compiler options.
+
+ Returns
+ -------
+ out: Data
+ The output data.
+ """
+ with transform.PassContext(opt_level=3, config={"relay.ext.verilator.options": opts}):
+ lib = relay.build(mod, target="llvm", params=params)
+ module = runtime.GraphModule(lib["default"](tvm.cpu()))
+ image_data = get_real_image(224, 224)
+ input_tensor = get_input_tensor_name()
+ module.set_input(input_tensor, image_data)
+ module.run()
+ out = module.get_output(0).asnumpy()
+ return out
+
+
+def get_labels():
+ """Return labels."""
+ label_file_url = "".join(
+ [
+ "https://raw.githubusercontent.com/",
+ "tensorflow/tensorflow/master/tensorflow/lite/java/demo/",
+ "app/src/main/assets/",
+ "labels_mobilenet_quant_v1_224.txt",
+ ]
+ )
+ label_file = "labels_mobilenet_quant_v1_224.txt"
+ label_path = download_testdata(label_file_url, label_file, module="data")
+ # List of 1001 classes
+ with open(label_path) as f:
+ labels = f.readlines()
+ return labels
+
+
+def check_result(res):
+ """Check prediction against labels."""
+ labels = get_labels()
+ predictions = np.squeeze(res)
+ prediction = np.argmax(predictions)
+ # 387 is the elephant
+ tvm.testing.assert_allclose(prediction, 387, rtol=1e-5, atol=1e-5)
Review comment:
In this case can't we just assert that prediction is equal to 387?
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[GitHub] [tvm] tmoreau89 commented on pull request #7972: [BYORTL][Verilator] update ops and add MobileNet
Posted by GitBox <gi...@apache.org>.
tmoreau89 commented on pull request #7972:
URL: https://github.com/apache/tvm/pull/7972#issuecomment-841864898
Thank you @vegaluisjose the changes LGTM. To alleviate @tqchen 's concerns can you comment on how long the simulations take on MobileNet? We're only simulating bias_add on a small RTL design so I presume the runtime won't be as long as some of the other TSIM tests on full VTA designs offloading entire conv2ds but let's make sure we keep tabs on runtime. Thanks!
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