From c74764bac32f2e89ccf225adb71f9d6720834367 Mon Sep 17 00:00:00 2001
From: George Hotz <george@comma.ai>
Date: Sun, 25 Oct 2020 08:28:18 -0700
Subject: [PATCH] oops, set to None

---
 README.md               | 5 -----
 test/test_conv_speed.py | 2 +-
 tinygrad/utils.py       | 2 +-
 3 files changed, 2 insertions(+), 7 deletions(-)

diff --git a/README.md b/README.md
index 0e998f12..5d54e7e8 100644
--- a/README.md
+++ b/README.md
@@ -67,8 +67,3 @@ loss.backward()
 optim.step()
 ```
 
-### TODO (to make real neural network library)
-
-* Implement gradcheck (numeric)
-* Make convolutions not slow while removing lines of code (NO CYTHON!)
-
diff --git a/test/test_conv_speed.py b/test/test_conv_speed.py
index 5f116995..a68f6f5d 100644
--- a/test/test_conv_speed.py
+++ b/test/test_conv_speed.py
@@ -6,7 +6,7 @@ try:
   builtins.__dict__['profile'] = prof
   # add @profile decorator to probe
 except ImportError:
-  pass
+  prof = None
 
 import cProfile
 import unittest
diff --git a/tinygrad/utils.py b/tinygrad/utils.py
index 57c65fc0..833b1d1f 100644
--- a/tinygrad/utils.py
+++ b/tinygrad/utils.py
@@ -34,11 +34,11 @@ def fetch_mnist():
 def im2col(x, H, W):
   bs,cin,oy,ox = x.shape[0], x.shape[1], x.shape[2]-(H-1), x.shape[3]-(W-1)
 
+  # TODO: use something like np.take for speed
   tx = np.empty((bs, oy, ox, cin*W*H), dtype=x.dtype)
   for Y in range(oy):
     for X in range(ox):
       tx[:, Y, X] = x[:, :, Y:Y+H, X:X+W].reshape(bs, -1)
-
   return tx.reshape(-1, cin*W*H)
 
 def col2im(tx, H, W, OY, OX):