upgrade to new python client

Author: hhsecond

python_client/sklearn_boston_house_price_prediction.py

@@ -18,6 +18,6 @@
 con = Client(host=arguments.host, port=arguments.port)
 con.tensorset('tensor', tensor)
 con.modelset('model', Backend.onnx, device, model)
-con.modelrun('model', input=['tensor'], output=['out'])
+con.modelrun('model', inputs=['tensor'], outputs=['out'])
 out = con.tensorget('out', as_type=BlobTensor)
 print(out.to_numpy())

python_client/spark_linear_regression.py

@@ -11,7 +11,7 @@
     device = rai.Device.cpu
 
 con = rai.Client(host=arguments.host, port=arguments.port)
-con.modelset("spark_model", rai.Backend.onnx, device, model, input=['features'])
+con.modelset("spark_model", rai.Backend.onnx, device, model, inputs=['features'])
 dummydata = [15.0]
 tensor = rai.Tensor.scalar(rai.DType.float, *dummydata)
 con.tensorset("input", tensor)

python_client/tensorflow_imagenet.py

@@ -26,7 +26,7 @@
 
 out1 = con.modelset(
     'imagenet_model', rai.Backend.tf, device,
-    input=['images'], output=['output'], data=tf_model)
+    inputs=['images'], outputs=['output'], data=tf_model)
 out2 = con.scriptset('imagenet_script', device, script)
 a = time.time()
 tensor = rai.BlobTensor.from_numpy(image)

python_client/tensorflow_tinyyolo.py

@@ -51,7 +51,7 @@
 tensor = rai.BlobTensor.from_numpy(img)
 con.tensorset('in', tensor)
 con.modelrun('yolo', 'in', 'out')
-con.scriptrun('yolo-post', 'boxes_from_tf', input='out', output='boxes')
+con.scriptrun('yolo-post', 'boxes_from_tf', inputs='out', outputs='boxes')
 boxes = con.tensorget('boxes', as_type=rai.BlobTensor).to_numpy()
 
 n_boxes = 0

python_client/torch_charrnn.py

@@ -33,5 +33,5 @@ def int2str(int_data):
 out3 = con.tensorset('prime', prime_tensor)
 out4 = con.modelrun('charRnn', ['prime', 'hidden'], ['out'])
 out5 = con.tensorget('out')
-para = int2str(out5.value)
+para = int2str(out5)
 print(para)

python_client/torch_imagenet.py

@@ -32,6 +32,6 @@
 out5 = con.modelrun('imagenet_model', 'temp1', 'temp2')
 out6 = con.scriptrun('imagenet_script', 'post_process', 'temp2', 'out')
 final = con.tensorget('out')
-ind = final.value[0]
+ind = final[0]
 print(ind, class_idx[str(ind)])
 print(time.time() - a)

requirements.txt

@@ -1,68 +1,20 @@
-absl-py==0.7.1
-astor==0.7.1
-certifi==2019.6.16
-cffi==1.12.3
-chardet==3.0.4
-cloudpickle==1.1.1
+certifi==2019.9.11
 cycler==0.10.0
-cytoolz==0.9.0.1
-dask==1.2.2
 decorator==4.4.0
-gast==0.2.2
-grpcio==1.16.1
-h5py==2.9.0
 hiredis==1.0.0
-idna==2.8
-imageio==2.5.0
-joblib==0.13.2
-Keras==2.2.4
-Keras-Applications==1.0.8
-Keras-Preprocessing==1.1.0
-keras2onnx==1.5.0
+imageio==2.6.1
 kiwisolver==1.1.0
-Markdown==3.1.1
-matplotlib==3.1.0
-mkl-fft==1.0.12
-mkl-random==1.0.2
-mock==3.0.5
-networkx==2.3
-numpy==1.16.4
-olefile==0.46
-onnx==1.5.0
-onnxconverter-common==1.5.0
-onnxmltools==1.5.0
-pandas==0.24.2
-Pillow==6.0.0
-protobuf==3.8.0
-py4j==0.10.7
-pycparser==2.19
-pyparsing==2.4.0
-pyspark==2.4.3
+matplotlib==3.1.1
+ml2rt==0.1.1
+networkx==2.4
+numpy==1.17.3
+Pillow==6.2.0
+pyparsing==2.4.2
 python-dateutil==2.8.0
-pytz==2019.1
-PyWavelets==1.0.3
-PyYAML==5.1.1
-redis==3.2.1
-redisai
-ml2rt
-requests==2.22.0
+PyWavelets==1.1.1
+redis==3.3.11
+redisai==0.4.0
 rmtest==0.7.0
-scikit-image==0.15.0
-scikit-learn==0.21.2
-scipy==1.2.1
-sip==4.19.13
+scikit-image==0.16.1
+scipy==1.3.1
 six==1.12.0
-skl2onnx==1.5.0
-tensorboard==1.13.1
-tensorflow==1.13.1
-tensorflow-estimator==1.13.0
-tensorflow-hub==0.4.0
-termcolor==1.1.0
-toolz==0.9.0
-torch==1.1.0
-torchvision==0.3.0
-tornado==6.0.2
-typing==3.7.4
-typing-extensions==3.7.4
-urllib3==1.25.3
-Werkzeug==0.15.4