#dataset.apply(partial(normalize_pressure_value, max_pressure_val=512))
dataset.apply(partial(spline_interpolate_and_resample, num_samples=NUM_SAMPLES))
dataset.expand_many(partial(rotate_digit, degrees=[5, 10, 15, 45, -5, -10, -15, -45]))
dataset.expand(reverse_digit_sequence)
# dataset.apply(lambda digit: convert_xy_to_derivative(digit, normalize=False))
#dataset.apply(partial(convert_xy_to_derivative, normalize=True))
#%% Split Train, Valid, Test
# Imports
import numpy as np
from sklearn.model_selection import train_test_split
X_train_valid = np.array(dataset.train_data)
X_test = np.array(dataset.test_data)
# Convert labels to numpy array and OneHot encode them
encoder, train_valid_labels, _, Y_test = dataset.onehot_encode_labels()
train_valid_labels = train_valid_labels.astype('float32').todense()
Y_test = Y_test.astype('float32').todense()
# Split Data
X_train, X_valid, Y_train, Y_valid = train_test_split(X_train_valid, train_valid_labels, shuffle=True, stratify=train_valid_labels, random_state=42)
#X_train, X_valid, Y_train, Y_valid = train_test_split(X_train_valid, Y_train_valid, shuffle=True, stratify=Y_train_valid, random_state=42)
#%% Model Training
from models.naive_gru import NaiveGRU
mymodel = NaiveGRU(X_train.shape[1:])
mymodel.batch_size = PARAM_BATCH_SIZE
mymodel.num_epochs = PARAM_NUM_EPOCHS
mymodel.initialize()
print(mymodel)
dataset.expand_many(partial(rotate_digit, degrees=ANGLES_TO_ROTATE))
dataset.expand(reverse_digit_sequence)
print("Training Data Len:", len(dataset.train_data))
print("Validation Data Len:", len(dataset.valid_data))
print("Test Data Len:", len(dataset.test_data))
#%%
import numpy as np
X_train = np.array(dataset.train_data)
X_valid = np.array(dataset.valid_data)
X_test = np.array(dataset.test_data)
# Convert labels to numpy array and OneHot encode them
encoder, Y_train, Y_valid, Y_test = dataset.onehot_encode_labels()
print("Training Data Shape:", X_train.shape)
print("Training Labels Shape:", Y_train.shape)
print("Validation Data Shape:", X_valid.shape)
print("Validation Labels Shape:", Y_valid.shape)
print("Test Data Shape:", X_test.shape)
print("Test Labels Shape:", Y_test.shape)
#%%
PARAM_NUM_EPOCHS = 70
PARAM_BATCH_SIZE = 500
from models.regularized_3x512_gru import Regularized3x512GRU
import os.path
