Hi,
I have written very simple Keras Neural Network
from numpy import loadtxt
from keras.models import Sequential
from keras.layers import Dense
# load the dataset
dataset = loadtxt('pima-indians-diabetes.csv', delimiter=',')
# split into input (X) and output (y) variables
X = dataset[:,0:8]
y = dataset[:,8]
print("X Shape", X.shape)
print("Y shape", y.shape)
# define the keras model
model = Sequential()
model.add(Dense(12, input_dim=8, activation='relu'))
model.add(Dense(8, activation='relu'))
model.add(Dense(1, activation='sigmoid'))
# compile the keras model
model.compile(loss='binary_crossentropy', optimizer='adam', metrics=['accuracy'])
# fit the keras model on the dataset
model.fit(X, y, epochs=150, batch_size=10, verbose=0)
model.save("my_model2.h5")
print("Saved model to disk")
To compile this with TVM I have written following code
data = np.array([6, 148, 72, 35, 0, 33.6, 0.627, 50])
print("input_1", data.shape) # (8,) (1,8)
data = data.reshape(1,8)
reconstructed_model = keras.models.load_model("my_model2.h5")
shape_dict = {"X": data.shape}
mod, params = relay.frontend.from_keras(reconstructed_model, shape_dict)
Which result s in following error
File "/home/kpit/tvm/tvm/src/relay/transforms/type_infer.cc", line 611
TVMError: Check failed: checked_type.as() == nullptr: Cannot resolve type of Var(dense_1_input) at (nullptr)
Request help here, as I am stuck.