Keras model tensorflow lite conversion input shape
0
I'm trying to convert my simple Keras model frozen graph to tensorflowlite but I'm not sure what the input shape is.
toco
--input_file='my_model.pb'
--input_format=TENSORFLOW_GRAPHDEF
--output_format=TFLITE
--output_file=/tmp/my_model.tflite
--inference_type=FLOAT
--input_type=FLOAT
--input_arrays=input_tensor
--output_arrays=output_tensor
--input_shapes=0,4,2851
My model is:
# create model
model = Sequential()
model.add(Dense(50, activation="tanh", input_dim=4, kernel_initializer="random_uniform", name="input_tensor"))
model.add(Dense(50, activation="tanh", kernel_initializer="random_uniform"))
model.add(Dense(1, activation="linear", kernel_initializer='random_uniform', name="output_tensor"))
android tensorflow keras asked Nov 15 '18 at 4:11
user3138464user3138464
12
add a comment |
0
I'm trying to convert my simple Keras model frozen graph to tensorflowlite but I'm not sure what the input shape is.
toco
--input_file='my_model.pb'
--input_format=TENSORFLOW_GRAPHDEF
--output_format=TFLITE
--output_file=/tmp/my_model.tflite
--inference_type=FLOAT
--input_type=FLOAT
--input_arrays=input_tensor
--output_arrays=output_tensor
--input_shapes=0,4,2851
My model is:
# create model
model = Sequential()
model.add(Dense(50, activation="tanh", input_dim=4, kernel_initializer="random_uniform", name="input_tensor"))
model.add(Dense(50, activation="tanh", kernel_initializer="random_uniform"))
model.add(Dense(1, activation="linear", kernel_initializer='random_uniform', name="output_tensor"))
asked Nov 15 '18 at 4:11
user3138464user3138464
12
input_dim=4means that each sample has a shape of(4,), i.e. is a vector of length 4.
– today
Nov 15 '18 at 5:17
I tried putting: input_shapes=1,4 for toco conversion but I'm still receiving a syntax error
– user3138464
Nov 16 '18 at 3:35
add a comment |
0
0
0
I'm trying to convert my simple Keras model frozen graph to tensorflowlite but I'm not sure what the input shape is.
toco
--input_file='my_model.pb'
--input_format=TENSORFLOW_GRAPHDEF
--output_format=TFLITE
--output_file=/tmp/my_model.tflite
--inference_type=FLOAT
--input_type=FLOAT
--input_arrays=input_tensor
--output_arrays=output_tensor
--input_shapes=0,4,2851
My model is:
# create model
model = Sequential()
model.add(Dense(50, activation="tanh", input_dim=4, kernel_initializer="random_uniform", name="input_tensor"))
model.add(Dense(50, activation="tanh", kernel_initializer="random_uniform"))
model.add(Dense(1, activation="linear", kernel_initializer='random_uniform', name="output_tensor"))
asked Nov 15 '18 at 4:11
user3138464user3138464
12
I'm trying to convert my simple Keras model frozen graph to tensorflowlite but I'm not sure what the input shape is.
toco
--input_file='my_model.pb'
--input_format=TENSORFLOW_GRAPHDEF
--output_format=TFLITE
--output_file=/tmp/my_model.tflite
--inference_type=FLOAT
--input_type=FLOAT
--input_arrays=input_tensor
--output_arrays=output_tensor
--input_shapes=0,4,2851
My model is:
# create model
model = Sequential()
model.add(Dense(50, activation="tanh", input_dim=4, kernel_initializer="random_uniform", name="input_tensor"))
model.add(Dense(50, activation="tanh", kernel_initializer="random_uniform"))
model.add(Dense(1, activation="linear", kernel_initializer='random_uniform', name="output_tensor"))
asked Nov 15 '18 at 4:11
user3138464user3138464
12
asked Nov 15 '18 at 4:11
user3138464user3138464
12
asked Nov 15 '18 at 4:11
user3138464user3138464
12
asked Nov 15 '18 at 4:11
user3138464user3138464
12
asked Nov 15 '18 at 4:11
user3138464user3138464
12
12
input_dim=4means that each sample has a shape of(4,), i.e. is a vector of length 4.
– today
Nov 15 '18 at 5:17
I tried putting: input_shapes=1,4 for toco conversion but I'm still receiving a syntax error
– user3138464
Nov 16 '18 at 3:35
add a comment |
input_dim=4means that each sample has a shape of(4,), i.e. is a vector of length 4.
– today
Nov 15 '18 at 5:17
I tried putting: input_shapes=1,4 for toco conversion but I'm still receiving a syntax error
– user3138464
Nov 16 '18 at 3:35
input_dim=4 means that each sample has a shape of (4,), i.e. is a vector of length 4.– today
Nov 15 '18 at 5:17
input_dim=4 means that each sample has a shape of (4,), i.e. is a vector of length 4.– today
Nov 15 '18 at 5:17
I tried putting: input_shapes=1,4 for toco conversion but I'm still receiving a syntax error
– user3138464
Nov 16 '18 at 3:35
I tried putting: input_shapes=1,4 for toco conversion but I'm still receiving a syntax error
– user3138464
Nov 16 '18 at 3:35
add a comment |
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input_dim=4means that each sample has a shape of(4,), i.e. is a vector of length 4.– today
Nov 15 '18 at 5:17
I tried putting: input_shapes=1,4 for toco conversion but I'm still receiving a syntax error
– user3138464
Nov 16 '18 at 3:35