LSTM cudnn test

2020-02-13 19:27:18 +01:00
parent 6a3b261bc9
commit c876fa05ae
10 changed files with 464 additions and 134 deletions
@@ -0,0 +1,74 @@
+import keras
+from keras.models import load_model
+import keras.backend.tensorflow_backend as KTF
+import numpy as np
+import argparse
+import tensorflow as tf
+import os
+import random
+import struct
+from keras.models import Sequential, Model
+
+def bin_write(f, data):
+    data = data.flatten()
+    fmt = 'f'*len(data)
+    bin = struct.pack(fmt, *data)
+    f.write(bin)
+
+
+if __name__ == '__main__':
+
+
+    print("DATA FORMAT: ", keras.backend.image_data_format())
+
+    print("Load model: ", "ferrariS1.hdf5")
+    model = load_model("ferrariS1.hdf5")
+    model.summary()
+
+    weights = model.get_weights()
+
+    x_angle = np.random.rand(1,100,4)
+    x_gyro = np.random.rand(1,100,3)
+    x_acc = np.random.rand(1,100,3)
+
+    [yhat_delta_p, yhat_delta_q] = model.predict([x_angle, x_gyro, x_acc], batch_size=1, verbose=1)
+
+    layer_name = 'bidirectional_3'
+    intermediate_layer_model = Model(inputs=model.input,
+                                     outputs=model.get_layer(layer_name).output)
+    intermediate_output = intermediate_layer_model.predict([x_angle, x_gyro, x_acc])
+
+    x_angle = np.array([x_angle])
+    x_gyro = np.array([x_gyro])
+    x_acc = np.array([x_acc])
+    intermediate_output = np.array([intermediate_output])
+
+    x_angle =  x_angle.transpose(0, 3, 1, 2)
+    x_gyro =  x_gyro.transpose(0, 3, 1, 2)
+    x_acc =  x_acc.transpose(0, 3, 1, 2)
+    intermediate_output = intermediate_output.transpose(0, 3, 1, 2)
+
+    print("x0: ", np.shape(x_angle))
+    print("out: ",np.shape(intermediate_output))
+
+    x_angle = np.array(x_angle.flatten(), dtype=np.float32)
+    x_gyro = np.array(x_gyro.flatten(), dtype=np.float32)
+    x_acc = np.array(x_acc.flatten(), dtype=np.float32)
+    yhat_delta_p = np.array(yhat_delta_p.flatten(), dtype=np.float32)
+    yhat_delta_q = np.array(yhat_delta_q.flatten(), dtype=np.float32)
+    intermediate_output = np.array(intermediate_output.flatten(), dtype=np.float32)
+
+
+    f = open("layers/input0.bin", mode='wb')
+    bin_write(f, x_angle)
+    f = open("layers/input1.bin", mode='wb')
+    bin_write(f, x_gyro)
+    f = open("layers/input2.bin", mode='wb')
+    bin_write(f, x_acc)
+    f = open("layers/output0.bin", mode='wb')
+    bin_write(f, yhat_delta_p)
+    f = open("layers/output1.bin", mode='wb')
+    bin_write(f, yhat_delta_q)
+    f = open("layers/output.bin", mode='wb')
+    bin_write(f, intermediate_output)
+