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Note 1.0 #1

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8bb76a9
Update RNN.py
NoteDance Jul 6, 2020
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Update FNN.py
NoteDance Jul 9, 2020
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Update CNN.py
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Update Note Architecture.py
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Update Note Architecture.py
NoteDance Jul 15, 2020
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Update FNN.py
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Update CNN.py
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Update RNN.py
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Update Note Architecture.py
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Update CNN.py
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Update CNN.py
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Update LSTM.py
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Update RNN.py
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Update Note Architecture.py
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Update FNN.py
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Update CNN.py
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Update Note Architecture.py
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Update FNN.py
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Update CNN.py
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Update RNN.py
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Update Note Architecture.py
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Update FNN.py
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Update CNN.py
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Update CNN.py
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Update GRU.py
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Update LSTM.py
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Update FNN.py
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Update CNN.py
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Update GRU.py
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Update LSTM.py
NoteDance Jul 26, 2020
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Update M_reluGRU.py
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Update RNN.py
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Update Note Architecture.py
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Update Note Architecture.py
NoteDance Jul 27, 2020
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363 changes: 180 additions & 183 deletions Note/create/Note Architecture.py
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18 changes: 9 additions & 9 deletions Note/create/RNN.py
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Original file line number Diff line number Diff line change
Expand Up @@ -114,7 +114,7 @@ def lstm_weight_x(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ig_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
og_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[2])
cltm_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return fg_weight_x,ig_weight_x,og_weight_x,cltm_weight_x
return [fg_weight_x,ig_weight_x,og_weight_x,cltm_weight_x]


def lstm_weight_h(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -128,7 +128,7 @@ def lstm_weight_h(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ig_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
og_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[2])
cltm_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return fg_weight_h,ig_weight_h,og_weight_h,cltm_weight_h
return [fg_weight_h,ig_weight_h,og_weight_h,cltm_weight_h]


def lstm_bias(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -142,7 +142,7 @@ def lstm_bias(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ig_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
og_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[2])
cltm_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return fg_bias,ig_bias,og_bias,cltm_bias
return [fg_bias,ig_bias,og_bias,cltm_bias]


def gru_weight_x(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -154,7 +154,7 @@ def gru_weight_x(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ug_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[0])
rg_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
cltm_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return ug_weight_x,rg_weight_x,cltm_weight_x
return [ug_weight_x,rg_weight_x,cltm_weight_x]


def gru_weight_h(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -166,7 +166,7 @@ def gru_weight_h(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ug_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[0])
rg_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
cltm_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return ug_weight_h,rg_weight_h,cltm_weight_h
return [ug_weight_h,rg_weight_h,cltm_weight_h]


def gru_bias(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -178,7 +178,7 @@ def gru_bias(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ug_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[0])
rg_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
cltm_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return ug_bias,rg_bias,cltm_bias
return [ug_bias,rg_bias,cltm_bias]


def m_relugru_weight_x(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -190,7 +190,7 @@ def m_relugru_weight_x(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ug_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[0])
rg_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
cltm_weight_x=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return ug_weight_x,rg_weight_x,cltm_weight_x
return [ug_weight_x,rg_weight_x,cltm_weight_x]


def m_relugru_weight_h(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -202,7 +202,7 @@ def m_relugru_weight_h(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ug_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[0])
rg_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
cltm_weight_h=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return ug_weight_h,rg_weight_h,cltm_weight_h
return [ug_weight_h,rg_weight_h,cltm_weight_h]


def m_relugru_bias(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
Expand All @@ -214,7 +214,7 @@ def m_relugru_bias(shape,mean=0,stddev=0.07,dtype=tf.float32,name=None):
ug_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[0])
rg_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[1])
cltm_bias=tf.Variable(tf.random.normal(shape=shape,mean=mean,stddev=stddev,dtype=dtype),name=name[3])
return ug_bias,rg_bias,cltm_bias
return [ug_bias,rg_bias,cltm_bias]


def word_emb(data,cword_weight):
Expand Down
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