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from cainvas import cpp2ipynb
cpp2ipynb("./asl_model/asl_model.cpp")

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import deepC
os.makedirs("./asl_model", exist_ok=True)

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import onnx
onnx_model=onnx.load_model("./asl_model.onnx")

# Check that the IR is well formed
import caffe2.python.onnx.backend as backend

for gesture, lbl in zip(inputs_train, outputs_train) :
  gesture = gesture.astype(np.float32)

  onnx.checker.check_model(onnx_model)

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dummy_input = torch.randn(INPUT_LEN)
torch.onnx.export(model, (dummy_input), "./asl_model.onnx", verbose=True)

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evaluate_x = torch.from_numpy(np.array(inputs_train, dtype=np.float32))
evaluate_y = torch.from_numpy(outputs_train)
if cuda:
  evaluate_x, evaluate_y = evaluate_x.cuda(), evaluate_y.cuda()

model.eval()
output = model(evaluate_x)
pred = output.data.max(1)[1]
#print(pred)
d = pred.eq(evaluate_y.data).cpu()

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EPOCHS = 150


for epoch in range(EPOCHS):
  model.train()
  running_loss = 0.0
  for batch_idx, (data, target) in \
  enumerate(zip(inputs_train, np.expand_dims(outputs_train, axis=1))):
    # Get Samples
    data = torch.from_numpy(np.array(data, dtype=np.float32))

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class aslModel(nn.Module):
  def __init__(self):
    super(aslModel, self).__init__()
    self.fc1 = nn.Linear(INPUT_LEN, 128)
    self.fc2 = nn.Linear(128, 16)
    self.fc3 = nn.Linear(16, NUM_GESTURES)

  def forward(self, x):
    x = x.view((-1, INPUT_LEN))
    h = F.relu(self.fc1(x))

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# https://stackoverflow.com/a/37710486/2020087
num_inputs = len(inputs)
randomize = np.arange(num_inputs)
np.random.shuffle(randomize)

# Swap the consecutive indexes (0, 1, 2, etc) with the randomized indexes
inputs = inputs[randomize]
outputs = outputs[randomize]

# Split the recordings (group of samples) into three sets: training, testing and validation

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# Set a fixed random seed value, for reproducibility, this will allow us to get
# the same random numbers each time the notebook is run
SEED = 1337
np.random.seed(SEED)
cuda = torch.cuda.is_available()
torch.manual_seed(SEED)
if cuda:
    torch.cuda.manual_seed(SEED)

# the list of gestures 

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plot_gesture(
  ["https://cainvas-static.s3.amazonaws.com/media/user_data/cainvas-admin/hi.csv", 
  "https://cainvas-static.s3.amazonaws.com/media/user_data/cainvas-admin/sup.csv"], 
  ["hi.csv", "sup.csv"], 
  "Gyroscope"
)