def test_Pooling():
np.random.seed(1)
A_prev = np.random.randn(1, 5, 5, 3)
hparameters = {"stride": 1, "f": 2}
max_output = pool_forward(A_prev, hparameters)
np.testing.assert_array_equal(Pooling(A_prev[0, :, :, :], hparameters),
max_output[0, :, :, :])
def layerResult(self, layer, X, pos):
"""
layer-dictonary l_type,kernel,hparams
X-numpy array(n_H_prev, n_W_prev, n_C_prev)
pooling-
X-numpy array(n_H_prev, n_W_prev, n_C_prev)
hparameters-"f" and "stride"
Pooling(X,hparameters,mode="max")
conv
vecConv(X,kernel,hparameters):
X- numpy arrya shape (n_H_prev, n_W_prev, n_C_prev)
kernel-numpy array of shape (f, f, n_C_prev, n_C)
hparameters-- python dictinory containing stride and pad
"""
if (layer["l_type"] == "conv"):
w = kernels[layer["kernel"]]
hparam = layer["hparams"]
return vecConv(X, w[:, :, :, pos[0]:pos[1]], hparam)
else:
hparam = layer["hparams"]
mode = layer["l_type"]
#batch size of 1
return Pooling(X[:, :, pos[0]:pos[1]], hparam, mode)
data_variable={"data":X,"pos":a,"layer":layer}
a=(start,end)
layer={"l_type":"conv","kernel":"W1","hparams":{"stride":1,"pad":0}}
pooling layer testing
layer2={"l_type":"max","hparams":{"stride":1,"f":2}}
"""
c, addr = s.accept()
#receive data from client
tic = time.process_time()
data_variable = receive_array(data, payload_size, c)
print('Connect with', addr, data_variable["data"].shape)
#imgout=y.conv_forward(data_variable["data"], w.W1[:,:,:,data_variable["pos"]:], w.b1[:,:,:,data_variable["pos"]:],data_variable["hpara"])
#out={"data":imgout}
X = data_variable["data"]
hparam = data_variable["layer"]["hparams"]
mode = data_variable["layer"]["l_type"]
if (mode == "conv"):
pos = data_variable["pos"]
w = kernels[data_variable["layer"]["kernel"]]
out = vecConv(X, w[:, :, :, pos[0]:pos[1]], hparam)
else:
out = Pooling(X, hparam, mode)
dout = {"data": out}
send(c, dout)
toc = time.process_time()
print("Computation time for conv part2 = " + str(1000 * (toc - tic)) +
"ms")
#send data to client
#c.send(bytes("Welcome to server",'utf-8'))
c.close()
while True:
"""
data_variable={"data":X,"pos":a,"layer":layer}
a=(start,end)
layer={"l_type":"conv","kernel":"W1","hparams":{"stride":1,"pad":0}}
pooling layer testing
layer2={"l_type":"max","hparams":{"stride":1,"f":2}}
"""
c, addr = s.accept()
#receive data from client
tic = time.process_time()
data_variable = receive_array(data, payload_size, c)
print('Connect with', addr, data_variable["data"].shape)
#imgout=y.conv_forward(data_variable["data"], w.W1[:,:,:,data_variable["pos"]:], w.b1[:,:,:,data_variable["pos"]:],data_variable["hpara"])
#out={"data":imgout}
pos = data_variable["pos"]
hparam = data_variable["layer"]["hparams"]
mode = data_variable["layer"]["l_type"]
if (mode == "conv"):
out = vecConv(X, w[:, :, :, pos[0]:pos[1]], hparam)
else:
out = Pooling(X[:, :, pos[0]:pos[1]], hparam, mode)
send(c, out)
toc = time.process_time()
print("Computation time for conv part2 = " + str(1000 * (toc - tic)) +
"ms")
#send data to client
#c.send(bytes("Welcome to server",'utf-8'))
c.close()