diff --git a/m.py b/m.py
index 7b41960..3628340 100644
--- a/m.py
+++ b/m.py
@@ -17,10 +17,10 @@ def conv(i, n, s, t = (1, 1)):
     return kl.Activation('relu')(b)
 
 def avg(i, s):
-    return kl.AveragePooling2D(s, padding = 'same')(i)
+    return kl.AveragePooling2D(s, padding = 'same', strides = (1, 1))(i)
 
 def max(i, s):
-    return kl.MaxPooling2D(s, padding = 'same')(i)
+    return kl.MaxPooling2D(s, padding = 'same', strides = (1, 1))(i)
 
 def generate_start(i):
     r1 = conv(i, CONV_SIZE, (3, 3))
@@ -113,7 +113,7 @@ def generate_type_c(i):
     c31 = max(i, (3, 3))
     c32 = conv(c31, CONV_SIZE, (1, 1))
 
-    c41 = conv(i, CONV_SIZE, (1, 1))
+    c41 = conv(i, CONV_SIZE, (1, 1), (3, 3))
 
     return kl.Concatenate()([c14, c23, c32, c41])
 
@@ -127,23 +127,23 @@ def generate_finish(i):
     return kl.Dense(TOUT_AMNT)(f5)
 
 
-gi = kl.Input((300, 300, 3))
+gi = kl.Input((2048, 2048, 3))
 
 ds = generate_start(gi)
 
-for _ in range(5):
+for _ in range(1):
     ds = generate_type_a(ds)
 
 ds = generate_ab_bridge(ds)
 
-for _ in range(4):
+for _ in range(1):
     ds = generate_type_b(ds)
 
 uo = generate_aux(ds)
 
 go = generate_bc_bridge(ds)
 
-for _ in range(2):
+for _ in range(1):
     go = generate_type_c(go)
 
 go = generate_finish(go)
@@ -151,4 +151,4 @@ go = generate_finish(go)
 mod = k.Model(inputs = gi, outputs = [go, uo])
 
 mod.summary()
-mod.compile(optimizer = ko.Lion(learning_rate = 0.001))
+mod.compile(optimizer = ko.Lion(learning_rate = 0.001), metrics = ['accuracy', 'val_accuracy'])