From 9c80cb063d37e11e509b02a5f149afaa85501775 Mon Sep 17 00:00:00 2001
From: Yuanjing Shi <ys26@tyler.cs.illinois.edu>
Date: Thu, 20 Feb 2020 22:47:58 -0600
Subject: [PATCH] Change README.md and onnx_environment.yml Clear up frontend/
Committer: Yuanjing Shi <ys26@tyler.cs.illinois.edu> On branch onnx_frontend
Changes to be committed: modified: README.md renamed:
onnx2hpvm/__init__.py -> frontend/__init__.py new file: frontend/common.py
new file: frontend/keras_frontend/__init__.py
---
hpvm/projects/onnx/README.md | 6 +-
.../onnx/{onnx2hpvm => frontend}/__init__.py | 0
hpvm/projects/onnx/frontend/common.py | 4 +
.../onnx/frontend/keras_frontend/__init__.py | 0
.../keras_frontend/approxhpvm_translator.py | 13 +-
.../keras_frontend/hpvm_dfg_translator.py | 0
.../keras_frontend/promise_translator.py | 0
.../keras_frontend/quantize_utils.py | 0
.../onnx/frontend/keras_frontend/util.py | 130 ++++++++++++++++++
.../keras_frontend/utils.py | 0
.../keras_frontend/weight_utils.py | 0
.../onnx/{onnx2hpvm => frontend}/mnist.py | 5 +-
.../onnx/frontend/onnx_frontend/__init__.py | 0
.../onnx_frontend/graph_builder.py} | 77 ++---------
.../onnx/frontend/onnx_frontend/util.py | 62 +++++++++
.../alexnet/{model.onnx => alexnet.onnx} | Bin
.../{resnet50v1.onnx => resnet50.onnx} | Bin
hpvm/projects/onnx/onnx_environment.yml | 9 +-
hpvm/projects/onnx/setup.py | 6 +-
.../.ipynb_checkpoints/mnist-checkpoint.ipynb | 103 +++++++++++++-
.../onnx/{keras_ref => }/src/alexnet.py | 7 +-
.../onnx/{keras_ref => }/src/alexnet2.py | 0
.../onnx/{keras_ref => }/src/lenet.py | 0
.../{keras_ref => }/src/mobilenet_cifar10.py | 0
.../{keras_ref => }/src/mobilenet_shallow.py | 0
.../src/mobilenetv2_cifar10.py | 0
.../onnx/{keras_ref => }/src/resnet.py | 0
.../onnx/{keras_ref => }/src/vgg16_cifar10.py | 0
.../{keras_ref => }/src/vgg16_cifar100.py | 0
29 files changed, 340 insertions(+), 82 deletions(-)
rename hpvm/projects/onnx/{onnx2hpvm => frontend}/__init__.py (100%)
create mode 100644 hpvm/projects/onnx/frontend/common.py
create mode 100644 hpvm/projects/onnx/frontend/keras_frontend/__init__.py
rename hpvm/projects/onnx/{keras_ref => frontend}/keras_frontend/approxhpvm_translator.py (98%)
rename hpvm/projects/onnx/{keras_ref => frontend}/keras_frontend/hpvm_dfg_translator.py (100%)
rename hpvm/projects/onnx/{keras_ref => frontend}/keras_frontend/promise_translator.py (100%)
rename hpvm/projects/onnx/{keras_ref => frontend}/keras_frontend/quantize_utils.py (100%)
create mode 100644 hpvm/projects/onnx/frontend/keras_frontend/util.py
rename hpvm/projects/onnx/{keras_ref => frontend}/keras_frontend/utils.py (100%)
rename hpvm/projects/onnx/{keras_ref => frontend}/keras_frontend/weight_utils.py (100%)
rename hpvm/projects/onnx/{onnx2hpvm => frontend}/mnist.py (81%)
create mode 100644 hpvm/projects/onnx/frontend/onnx_frontend/__init__.py
rename hpvm/projects/onnx/{onnx2hpvm/frontend.py => frontend/onnx_frontend/graph_builder.py} (62%)
create mode 100644 hpvm/projects/onnx/frontend/onnx_frontend/util.py
rename hpvm/projects/onnx/models/alexnet/{model.onnx => alexnet.onnx} (100%)
rename hpvm/projects/onnx/models/resnet50/{resnet50v1.onnx => resnet50.onnx} (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/alexnet.py (97%)
rename hpvm/projects/onnx/{keras_ref => }/src/alexnet2.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/lenet.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/mobilenet_cifar10.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/mobilenet_shallow.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/mobilenetv2_cifar10.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/resnet.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/vgg16_cifar10.py (100%)
rename hpvm/projects/onnx/{keras_ref => }/src/vgg16_cifar100.py (100%)
diff --git a/hpvm/projects/onnx/README.md b/hpvm/projects/onnx/README.md
index d9214dbdb0..9cbaeb59ce 100644
--- a/hpvm/projects/onnx/README.md
+++ b/hpvm/projects/onnx/README.md
@@ -1,7 +1,11 @@
## Importing Conda Environment:
-conda env create -f keras_environment.yml
+conda env create -f onnx\_environment.yml
+
+## Activate/deactivate Conda Environment
+
+conda activate onnx\_env
## Building and Installing Frontend:
diff --git a/hpvm/projects/onnx/onnx2hpvm/__init__.py b/hpvm/projects/onnx/frontend/__init__.py
similarity index 100%
rename from hpvm/projects/onnx/onnx2hpvm/__init__.py
rename to hpvm/projects/onnx/frontend/__init__.py
diff --git a/hpvm/projects/onnx/frontend/common.py b/hpvm/projects/onnx/frontend/common.py
new file mode 100644
index 0000000000..fb4f90465d
--- /dev/null
+++ b/hpvm/projects/onnx/frontend/common.py
@@ -0,0 +1,4 @@
+import sys
+import os
+
+
diff --git a/hpvm/projects/onnx/frontend/keras_frontend/__init__.py b/hpvm/projects/onnx/frontend/keras_frontend/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/hpvm/projects/onnx/keras_ref/keras_frontend/approxhpvm_translator.py b/hpvm/projects/onnx/frontend/keras_frontend/approxhpvm_translator.py
similarity index 98%
rename from hpvm/projects/onnx/keras_ref/keras_frontend/approxhpvm_translator.py
rename to hpvm/projects/onnx/frontend/keras_frontend/approxhpvm_translator.py
index f5026d8405..309feb4ee0 100644
--- a/hpvm/projects/onnx/keras_ref/keras_frontend/approxhpvm_translator.py
+++ b/hpvm/projects/onnx/frontend/keras_frontend/approxhpvm_translator.py
@@ -1,10 +1,10 @@
import sys
import numpy as np
-from frontend.promise_translator import PromiseRtTranslator
-from frontend.hpvm_dfg_translator import HPVMTranslator
-from frontend.weight_utils import dumpLabels, dumpData, dumpConvWeights, dumpFcWeights, dumpFcBias
-from frontend.utils import *
+from .promise_translator import PromiseRtTranslator
+from .hpvm_dfg_translator import HPVMTranslator
+from .weight_utils import dumpLabels, dumpData, dumpConvWeights, dumpFcWeights, dumpFcBias
+from .utils import *
import keras
import os
@@ -926,6 +926,9 @@ def getUniquePath(weights_dir):
#***** Top level External Function *******
+'''
+This code is refactored into keras_frontend.py
+Use of func "translate_to_approxhpvm" from this .py file is deprecated
def translate_to_approxhpvm(model, weights_dir, test_data=None, test_labels=None,
num_classes=10, reload_dir=None):
@@ -964,5 +967,5 @@ def translate_to_approxhpvm(model, weights_dir, test_data=None, test_labels=None
filter_names = tensorRtTranslator.getFilterNames()
hpvmTranslator = HPVMTranslator(dfg, weight_str, input_str, filter_names)
hpvmTranslator.translate(model, weights_dir, test_data)
-
+'''
diff --git a/hpvm/projects/onnx/keras_ref/keras_frontend/hpvm_dfg_translator.py b/hpvm/projects/onnx/frontend/keras_frontend/hpvm_dfg_translator.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/keras_frontend/hpvm_dfg_translator.py
rename to hpvm/projects/onnx/frontend/keras_frontend/hpvm_dfg_translator.py
diff --git a/hpvm/projects/onnx/keras_ref/keras_frontend/promise_translator.py b/hpvm/projects/onnx/frontend/keras_frontend/promise_translator.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/keras_frontend/promise_translator.py
rename to hpvm/projects/onnx/frontend/keras_frontend/promise_translator.py
diff --git a/hpvm/projects/onnx/keras_ref/keras_frontend/quantize_utils.py b/hpvm/projects/onnx/frontend/keras_frontend/quantize_utils.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/keras_frontend/quantize_utils.py
rename to hpvm/projects/onnx/frontend/keras_frontend/quantize_utils.py
diff --git a/hpvm/projects/onnx/frontend/keras_frontend/util.py b/hpvm/projects/onnx/frontend/keras_frontend/util.py
new file mode 100644
index 0000000000..ca8e0d1ded
--- /dev/null
+++ b/hpvm/projects/onnx/frontend/keras_frontend/util.py
@@ -0,0 +1,130 @@
+import sys
+import numpy as np
+from ..approxhpvm_translator import DFG, DFGNode
+from ..promise_translator import PromiseRtTranslator
+from ..hpvm_dfg_translator import HPVMTranslator
+from ..weight_utils import dumpLabels, dumpData, dumpConvWeights, dumpFcWeights, dumpFcBias
+from ..utils import *
+import keras
+import os
+
+
+
+def reloadModelParams(model, reload_dir, x_test, y_test):
+
+ print ("\n\n*****NOTE: Reloading pre-trained weights \n")
+
+ score = model.evaluate(x_test, y_test, verbose=0)
+ print('Test loss2:', score[0])
+ print('Test accuracy2:', score[1])
+
+ for i in range(len(model.layers)):
+ layer = model.layers[i]
+ layer_name = layer.name
+ print ("*layer_name = ", layer_name)
+
+ if "conv" not in layer_name and "dense" not in layer_name:
+ continue
+
+ w_path = reload_dir + layer_name + "_w.bin"
+ b_path = reload_dir + layer_name + "_b.bin"
+
+ print ("** w_path = ", w_path)
+ print ("** b_path = ", b_path)
+
+ w_arr = np.fromfile(w_path, dtype='float32')
+ b_arr = np.fromfile(b_path, dtype='float32')
+
+ w_shape = layer.get_weights()[0].shape
+ b_shape = layer.get_weights()[1].shape
+
+ if "conv" in layer_name:
+ w_nchw_shape = (w_shape[3], w_shape[2], w_shape[0], w_shape[1])
+ w_arr = np.reshape(w_arr, w_nchw_shape)
+ b_arr = np.reshape(b_arr, b_shape)
+
+ w_arr = np.transpose(w_arr, (2,3,1,0))
+ print ("old_shape = ", w_shape, " new_shape = ", w_arr.shape)
+
+ if "dense" in layer_name:
+ w_arr = np.reshape(w_arr, w_shape)
+ b_arr = np.reshape(b_arr, b_shape)
+
+ weights = []
+ weights.append(w_arr)
+ weights.append(b_arr)
+ # NOTE: overriding weights
+ layer.set_weights(weights)
+
+ score = model.evaluate(x_test, y_test, verbose=0)
+ print('Test loss2:', score[0])
+ print('Test accuracy2:', score[1])
+
+
+def getUniquePath(weights_dir):
+
+ # Do not overwrite existing directories - create new with unique ID
+ if os.path.exists(weights_dir):
+ char_count = len(weights_dir)
+ if weights_dir[char_count - 1] == "/":
+ weights_dir = weights_dir[:char_count-1]
+
+ tokens = weights_dir.split("_")
+ last_tok = tokens[len(tokens) - 1]
+ if last_tok.isdigit():
+ id = int(last_tok)
+ id += 1
+ weights_dir = "_".join(tokens[:-1]) + "_" + str(id) + "/"
+ else:
+ weights_dir = "_".join(tokens) + "_1/"
+
+ weights_dir = getUniquePath(weights_dir)
+
+ #print (weights_dir)
+
+ return weights_dir
+
+
+#***** Top level External Function *******
+def translate_to_approxhpvm(model,
+ weights_dir,
+ test_data=None,
+ test_labels=None,
+ num_classes=10,
+ reload_dir=None):
+
+
+ weights_dir = getUniquePath(weights_dir)
+ os.mkdir(weights_dir)
+
+
+ if reload_dir is not None:
+ y_test = keras.utils.to_categorical(test_labels, num_classes)
+ reloadModelParams(model, reload_dir, test_data, y_test)
+
+
+ dfg = DFG()
+ for i in range(len(model.layers)):
+ layer = model.layers[i]
+ # NOTE: Add DNN layer to graph
+ dfg.add_to_graph(layer)
+
+ # Build and Print DFG in reverse postorder
+ dfg.buildDFG()
+
+
+ print ("test_data.shape = ", test_data.shape, "\n")
+ print ("test_labels.shape = ", test_labels.shape, "\n")
+
+ tensorRtTranslator = TensorRtTranslator(dfg)
+ tensorRtTranslator.translate(model, weights_dir, test_data, test_labels)
+ weight_str = tensorRtTranslator.getWeightStr()
+ input_str = tensorRtTranslator.getInputStr()
+
+
+ promiseRtTranslator = PromiseRtTranslator(dfg, weight_str)
+ promiseRtTranslator.translate(model, weights_dir, test_data)
+
+ filter_names = tensorRtTranslator.getFilterNames()
+ hpvmTranslator = HPVMTranslator(dfg, weight_str, input_str, filter_names)
+ hpvmTranslator.translate(model, weights_dir, test_data)
\ No newline at end of file
diff --git a/hpvm/projects/onnx/keras_ref/keras_frontend/utils.py b/hpvm/projects/onnx/frontend/keras_frontend/utils.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/keras_frontend/utils.py
rename to hpvm/projects/onnx/frontend/keras_frontend/utils.py
diff --git a/hpvm/projects/onnx/keras_ref/keras_frontend/weight_utils.py b/hpvm/projects/onnx/frontend/keras_frontend/weight_utils.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/keras_frontend/weight_utils.py
rename to hpvm/projects/onnx/frontend/keras_frontend/weight_utils.py
diff --git a/hpvm/projects/onnx/onnx2hpvm/mnist.py b/hpvm/projects/onnx/frontend/mnist.py
similarity index 81%
rename from hpvm/projects/onnx/onnx2hpvm/mnist.py
rename to hpvm/projects/onnx/frontend/mnist.py
index 925fc8dc84..8a4f3a85d7 100644
--- a/hpvm/projects/onnx/onnx2hpvm/mnist.py
+++ b/hpvm/projects/onnx/frontend/mnist.py
@@ -8,9 +8,10 @@ from onnxruntime.backend.backend import OnnxRuntimeBackend as backend
from onnx import numpy_helper, version_converter
# onnx2hpvm modules
-from frontend import convert_to_hpvm
+from onnx_frontend.util import convert_to_hpvm
-model = onnx.load('../models/mnist/mnist.onnx')
+#model = onnx.load('../models/mnist/mnist.onnx')
+model = onnx.load('../models/alexnet/alexnet.onnx')
test_data_dir = '../models/mnist/test_data_set_0'
# print('The model before conversion:\n{}'.format(model))
diff --git a/hpvm/projects/onnx/frontend/onnx_frontend/__init__.py b/hpvm/projects/onnx/frontend/onnx_frontend/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/hpvm/projects/onnx/onnx2hpvm/frontend.py b/hpvm/projects/onnx/frontend/onnx_frontend/graph_builder.py
similarity index 62%
rename from hpvm/projects/onnx/onnx2hpvm/frontend.py
rename to hpvm/projects/onnx/frontend/onnx_frontend/graph_builder.py
index 1a14731876..2a4fb4d9b1 100644
--- a/hpvm/projects/onnx/onnx2hpvm/frontend.py
+++ b/hpvm/projects/onnx/frontend/onnx_frontend/graph_builder.py
@@ -6,7 +6,10 @@ class Node(object):
def __init__(self, name, shape, dtype):
self._name = name
self._shape = shape if shape else {}
- self_dtype = dtype
+ self._dtype = dtype
+ def __str__(self):
+ return "Node: " + self._name + " with shape: " + str(self._shape) + " and data type " + str(self._dtype)
+ __repr__ = __str__
class GraphBuilder(object):
@@ -22,15 +25,11 @@ class GraphBuilder(object):
self._shape = shape if shape else self._build_shape()
def build_cfg(self):
- # parse parameters
+ # parse init tensors
for init_tensor in self._graph.initializer:
if not init_tensor.name.strip():
raise ValueError("Tensor's name is required.")
- print(init_tensor.name)
- print("###############################")
self._params[init_tensor.name] = self._parse_array(init_tensor)
- print(self._params[init_tensor.name])
- print("###############################")
self._nodes[init_tensor.name] = Node(init_tensor.name,
self._params[init_tensor.name].shape,
self._params[init_tensor.name].dtype)
@@ -61,18 +60,23 @@ class GraphBuilder(object):
self._nodes[i_name] = Node(i_name,
tshape,
dtype)
+ for node in self._graph.node:
+ op_name = node.op_type
+ print("###############################")
+ print(op_name)
+ print(node.attribute)
+ print(node.input)
+ print(node.output)
print(self._nodes)
def _build_shape(self):
shape = {}
for input in self._graph.input:
- print (input.name, end=": ")
# get type of input tensor
tensor_type = input.type.tensor_type
# check if it has a shape:
if (tensor_type.HasField("shape")):
shape[input.name] = tensor_type.shape
- print(shape)
return shape
def _parse_array(self, tensor_proto):
@@ -98,59 +102,4 @@ class GraphBuilder(object):
from onnx.mapping import TENSOR_TYPE_TO_NP_TYPE
return TENSOR_TYPE_TO_NP_TYPE[value_proto.type.tensor_type.elem_type].name
except AttributeError:
- return dtype
-
-def convert_to_hpvm(model,
- shape=None,
- dtype="float32",
- opset=None):
- """Converting an onnx model to equivalent HPVM IR
-
- ONNX graphs are represented as Python Protobuf objects.
- The companion parameters will be handled automatically.
- However, the input names from onnx graph is vague, mixing inputs and
- network weights/bias such as "1", "2"...
- For convenience, we rename the `real` input names to "input_0",
- "input_1"... And renaming parameters to "param_0", "param_1"...
-
- Parameters
- ----------
- model : protobuf object
- ONNX ModelProto after ONNX v1.1.0
-
- shape : dict of str to tuple, optional
- The input shape to the graph
-
- dtype : str or dict of str to str
- The input types to the graph
-
- opset : int, optional
- Override to autodetected opset.
- This can be helpful for some testing.
-
- Returns
- -------
-
- """
- try:
- from onnx import checker, onnx_cpp2py_export
- if hasattr(checker, 'check_model'):
- # try use onnx's own model checker before converting any model
- try:
- checker.check_model(model)
- except onnx_cpp2py_export.checker.ValidationError as e:
- import warnings
- # the checker is a bit violent about errors, so simply print warnings here
- warnings.warn(str(e))
- except ImportError:
- pass
- print("onnx model is checked valid.")
- graph = model.graph
- if opset is None:
- try:
- opset = model.opset_import[0].version if model.opset_import else 1
- except AttributeError:
- opset = 1 # default opset version set to 1 if not specified
- print("opset version: ", opset)
- gb = GraphBuilder(model, shape, dtype, opset)
- gb.build_cfg()
\ No newline at end of file
+ return dtype
\ No newline at end of file
diff --git a/hpvm/projects/onnx/frontend/onnx_frontend/util.py b/hpvm/projects/onnx/frontend/onnx_frontend/util.py
new file mode 100644
index 0000000000..2900f2faf3
--- /dev/null
+++ b/hpvm/projects/onnx/frontend/onnx_frontend/util.py
@@ -0,0 +1,62 @@
+import sys
+import numpy as np
+import os
+from .graph_builder import GraphBuilder
+
+def check_model(onnx_model):
+ try:
+ from onnx import checker, onnx_cpp2py_export
+ if hasattr(checker, 'check_model'):
+ # try use onnx's own model checker before converting any model
+ try:
+ checker.check_model(onnx_model)
+ print("onnx model is checked valid.")
+ except onnx_cpp2py_export.checker.ValidationError as e:
+ import warnings
+ # the checker is a bit violent about errors, so simply print warnings here
+ warnings.warn(str(e))
+ except ImportError as e:
+ raise ImportError("Unable to import onnx.checker which is required {}".format(e))
+
+def convert_to_hpvm(model,
+ shape=None,
+ dtype="float32",
+ opset=None):
+ """Converting an onnx model to equivalent HPVM IR
+
+ ONNX graphs are represented as Python Protobuf objects.
+ The companion parameters will be handled automatically.
+ However, the input names from onnx graph is vague, mixing inputs and
+ network weights/bias such as "1", "2"...
+ For convenience, we rename the `real` input names to "input_0",
+ "input_1"... And renaming parameters to "param_0", "param_1"...
+
+ Parameters
+ ----------
+ model : protobuf object
+ ONNX ModelProto after ONNX v1.1.0
+
+ shape : dict of str to tuple, optional
+ The input shape to the graph
+
+ dtype : str or dict of str to str
+ The input types to the graph
+
+ opset : int, optional
+ Override to autodetected opset.
+ This can be helpful for some testing.
+
+ Returns
+ -------
+
+ """
+ check_model(model)
+ graph = model.graph
+ if opset is None:
+ try:
+ opset = model.opset_import[0].version if model.opset_import else 1
+ except AttributeError:
+ opset = 1 # default opset version set to 1 if not specified
+ print("opset version: ", opset)
+ gb = GraphBuilder(model, shape, dtype, opset)
+ gb.build_cfg()
\ No newline at end of file
diff --git a/hpvm/projects/onnx/models/alexnet/model.onnx b/hpvm/projects/onnx/models/alexnet/alexnet.onnx
similarity index 100%
rename from hpvm/projects/onnx/models/alexnet/model.onnx
rename to hpvm/projects/onnx/models/alexnet/alexnet.onnx
diff --git a/hpvm/projects/onnx/models/resnet50/resnet50v1.onnx b/hpvm/projects/onnx/models/resnet50/resnet50.onnx
similarity index 100%
rename from hpvm/projects/onnx/models/resnet50/resnet50v1.onnx
rename to hpvm/projects/onnx/models/resnet50/resnet50.onnx
diff --git a/hpvm/projects/onnx/onnx_environment.yml b/hpvm/projects/onnx/onnx_environment.yml
index 1f1d42b762..4953af48fc 100644
--- a/hpvm/projects/onnx/onnx_environment.yml
+++ b/hpvm/projects/onnx/onnx_environment.yml
@@ -77,7 +77,6 @@ dependencies:
- wheel=0.32.2=py36_0
- widgetsnbextension=3.4.2=py36_0
- xlwt=1.3.0=py36_0
- - _license=1.1=py36_1
- _tflow_select=2.1.0=gpu
- alabaster=0.7.12=py36_0
- anaconda-client=1.7.2=py36_0
@@ -230,7 +229,7 @@ dependencies:
- pcre=8.42=h439df22_0
- pep8=1.7.1=py36_0
- pillow=5.3.0=py36h34e0f95_0
- - pip=18.1=py36_0
+ - pip=20.0.2=py36_0
- pixman=0.34.0=hceecf20_3
- pkginfo=1.4.2=py36_1
- pluggy=0.8.0=py36_0
@@ -319,4 +318,10 @@ dependencies:
- msgpack==0.5.6
- tables==3.4.4
- torch==0.4.1
+ - fire==0.2.1
+ - keras2onnx==1.6.0
+ - onnxconverter-common==1.6.0
+ - onnxruntime==1.1.1
+ - onnxruntime-gpu==1.1.1
+
diff --git a/hpvm/projects/onnx/setup.py b/hpvm/projects/onnx/setup.py
index 8405aca7ec..7bcdce7a1d 100644
--- a/hpvm/projects/onnx/setup.py
+++ b/hpvm/projects/onnx/setup.py
@@ -2,11 +2,11 @@
from setuptools import setup
setup(
- name='onnx2hpvm',
+ name='frontend',
version='1.0',
- description='HPVM onnx frontend modules',
+ description='HPVM frontend modules',
author='Yuanjing Shi',
author_email='ys26@illinois.edu',
- packages=['onnx2hpvm'],
+ packages=['fronend'],
install_requires=[],
)
diff --git a/hpvm/projects/onnx/src/.ipynb_checkpoints/mnist-checkpoint.ipynb b/hpvm/projects/onnx/src/.ipynb_checkpoints/mnist-checkpoint.ipynb
index 2fd64429bf..bbac5d491d 100644
--- a/hpvm/projects/onnx/src/.ipynb_checkpoints/mnist-checkpoint.ipynb
+++ b/hpvm/projects/onnx/src/.ipynb_checkpoints/mnist-checkpoint.ipynb
@@ -1,6 +1,105 @@
{
- "cells": [],
- "metadata": {},
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "import sys\n",
+ "import numpy as np\n",
+ "import onnx\n",
+ "import glob\n",
+ "from onnxruntime.backend.backend import OnnxRuntimeBackend as backend\n",
+ "\n",
+ "from onnx import numpy_helper\n",
+ "\n",
+ "# onnx2hpvm modules\n",
+ "from onnx2hpvm.onnx_translator import from_onnx_to_hpvm"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "model = onnx.load('../models/mnist/mnist.onnx')\n",
+ "test_data_dir = '../models/mnist/test_data_set_0'"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "1\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Load inputs\n",
+ "inputs = []\n",
+ "inputs_num = len(glob.glob(os.path.join(test_data_dir, 'input_*.pb')))\n",
+ "print(inputs_num)\n",
+ "for i in range(inputs_num):\n",
+ " input_file = os.path.join(test_data_dir, 'input_{}.pb'.format(i))\n",
+ " tensor = onnx.TensorProto()\n",
+ " with open(input_file, 'rb') as f:\n",
+ " tensor.ParseFromString(f.read())\n",
+ " inputs.append(numpy_helper.to_array(tensor))\n",
+ "\n",
+ "# Load reference outputs\n",
+ "ref_outputs = []\n",
+ "ref_outputs_num = len(glob.glob(os.path.join(test_data_dir, 'output_*.pb')))\n",
+ "for i in range(ref_outputs_num):\n",
+ " output_file = os.path.join(test_data_dir, 'output_{}.pb'.format(i))\n",
+ " tensor = onnx.TensorProto()\n",
+ " with open(output_file, 'rb') as f:\n",
+ " tensor.ParseFromString(f.read())\n",
+ " ref_outputs.append(numpy_helper.to_array(tensor))\n",
+ "\n",
+ "# Run the model on the backend\n",
+ "outputs = list(backend.run_model(model, inputs))\n",
+ "\n",
+ "#from_onnx_to_hpvm(model)\n",
+ "# Compare the results with reference outputs.\n",
+ "#for ref_o, o in zip(ref_outputs, outputs):\n",
+ "# np.testing.assert_almost_equal(ref_o, o)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.7.3"
+ }
+ },
"nbformat": 4,
"nbformat_minor": 2
}
diff --git a/hpvm/projects/onnx/keras_ref/src/alexnet.py b/hpvm/projects/onnx/src/alexnet.py
similarity index 97%
rename from hpvm/projects/onnx/keras_ref/src/alexnet.py
rename to hpvm/projects/onnx/src/alexnet.py
index b1f29bfc05..feceaf99e6 100644
--- a/hpvm/projects/onnx/keras_ref/src/alexnet.py
+++ b/hpvm/projects/onnx/src/alexnet.py
@@ -1,6 +1,5 @@
import numpy as np
-
from keras.datasets import cifar10
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Flatten, Activation
@@ -17,8 +16,6 @@ import struct
import keras
import numpy as np
import os
-from frontend.approxhpvm_translator import translate_to_approxhpvm
-from frontend.weight_utils import dumpCalibrationData
@@ -171,3 +168,7 @@ if __name__ == "__main__":
model = buildModel2()
trainModel(model)
+ import keras2onnx
+ onnx_model = keras2onnx.convert_keras(model, model.name)
+ import onnx
+ onnx.save(onnx_model, "../models/keras/alexnet.onnx")
diff --git a/hpvm/projects/onnx/keras_ref/src/alexnet2.py b/hpvm/projects/onnx/src/alexnet2.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/alexnet2.py
rename to hpvm/projects/onnx/src/alexnet2.py
diff --git a/hpvm/projects/onnx/keras_ref/src/lenet.py b/hpvm/projects/onnx/src/lenet.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/lenet.py
rename to hpvm/projects/onnx/src/lenet.py
diff --git a/hpvm/projects/onnx/keras_ref/src/mobilenet_cifar10.py b/hpvm/projects/onnx/src/mobilenet_cifar10.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/mobilenet_cifar10.py
rename to hpvm/projects/onnx/src/mobilenet_cifar10.py
diff --git a/hpvm/projects/onnx/keras_ref/src/mobilenet_shallow.py b/hpvm/projects/onnx/src/mobilenet_shallow.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/mobilenet_shallow.py
rename to hpvm/projects/onnx/src/mobilenet_shallow.py
diff --git a/hpvm/projects/onnx/keras_ref/src/mobilenetv2_cifar10.py b/hpvm/projects/onnx/src/mobilenetv2_cifar10.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/mobilenetv2_cifar10.py
rename to hpvm/projects/onnx/src/mobilenetv2_cifar10.py
diff --git a/hpvm/projects/onnx/keras_ref/src/resnet.py b/hpvm/projects/onnx/src/resnet.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/resnet.py
rename to hpvm/projects/onnx/src/resnet.py
diff --git a/hpvm/projects/onnx/keras_ref/src/vgg16_cifar10.py b/hpvm/projects/onnx/src/vgg16_cifar10.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/vgg16_cifar10.py
rename to hpvm/projects/onnx/src/vgg16_cifar10.py
diff --git a/hpvm/projects/onnx/keras_ref/src/vgg16_cifar100.py b/hpvm/projects/onnx/src/vgg16_cifar100.py
similarity index 100%
rename from hpvm/projects/onnx/keras_ref/src/vgg16_cifar100.py
rename to hpvm/projects/onnx/src/vgg16_cifar100.py
--
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