Merge pull request #187 from facebookresearch/dock-fixes

Bunch of doc fixes and use correct reduction operators

Author: prigoyal

docs/source/framework/pytorch_integration/layers_database.rst

@@ -33,7 +33,7 @@ Average pooling
 .. code::
 
     def avgpool(float(B, C, H, W) input) -> (output) {{
-        output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+        output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
     }}
 
 
@@ -43,7 +43,7 @@ Max pooling
 .. code::
 
     def maxpool(float(B, C, H, W) input) -> (output) {{
-        output(b, c, h, w) max= input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+        output(b, c, h, w) max=! input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
     }}
 
 Convolution layers

docs/source/framework/pytorch_integration/writing_layers.rst

@@ -182,7 +182,7 @@ adopt whatever feels more convenient.
     import torch
     lang = """
     def avgpool(float(B, C, H, W) input) -> (output) {{
-        output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+        output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
     }}
     """
     avgpool = tc.define(lang, name="avgpool", constants={"sH":1, "sW":1, "kH":2, "kW":2})
@@ -205,7 +205,7 @@ adopt whatever feels more convenient.
     import re
     LANG="""
     def avgpool(float(B, C, H, W) input) -> (output) {
-        output(b, c, h, w) += input(b, c, h * <sh> + kh, w * <sw> + kw) where kh in 0:<kH>, kw in 0:<kW>
+        output(b, c, h, w) +=! input(b, c, h * <sh> + kh, w * <sw> + kw) / (<kH> * <kW>) where kh in 0:<kH>, kw in 0:<kW>
     }
     """
     sH, sW, kH, kW = 1, 1, 2, 2

tensor_comprehensions/library/layers.yaml

@@ -61,13 +61,13 @@
 - name: avgpool
   lang: |
     def avgpool(float(B, C, H, W) input) -> (output) {{
-      output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+      output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
     }}
 
 - name: maxpool
   lang: |
     def maxpool(float(B, C, H, W) input) -> (output) {{
-      output(b, c, h, w) max= input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+      output(b, c, h, w) max=! input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
     }}
 
 - name: scale

tensor_comprehensions/tc_unit.py

@@ -397,7 +397,7 @@ def __call__(self, *inputs, **kwargs):
 
                 * :attr:`conv`: if kernel resembles a convolution operation
 
-                * :attr:`group_conv`: if kernel resembles a convolution operation
+                * :attr:`group_conv`: if kernel resembles a group convolution operation
 
                 * :attr:`naive`: if none of the above, then chose naive *Default*
 
@@ -542,7 +542,7 @@ def autotune(self, *inputs, **kwargs):
 
                 * :attr:`conv`: if kernel resembles a convolution operation
 
-                * :attr:`group_conv`: if kernel resembles a convolution operation
+                * :attr:`group_conv`: if kernel resembles a group convolution operation
 
                 * :attr:`naive`: if none of the above, then chose naive *Default*
 

test_python/layers/test_avgpool.py

@@ -16,7 +16,6 @@
 import tensor_comprehensions as tc
 
 import torch
-import torch.cuda
 import unittest
 
 
@@ -26,7 +25,7 @@ def test_avgpool(self):
         # NOTE: take note of use of {{ }} below for handling TC with scalars
         LANG = """
         def avgpool(float(B, C, H, W) input) -> (output) {{
-            output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+            output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
         }}
         """
         avgpool = tc.define(LANG, name="avgpool", constants={"sH":1, "sW":1, "kH":2, "kW":2})

test_python/layers/test_avgpool_autotune.py

@@ -31,7 +31,7 @@ def test_avgpool_autotune(self):
         # NOTE: take note of use of {{ }} below for handling TC with scalars
         LANG = """
         def avgpool(float(B, C, H, W) input) -> (output) {{
-            output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+            output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
         }}
         """
         avgpool = tc.define(LANG, name="avgpool", constants={"sH":1, "sW":1, "kH":2, "kW":2})

test_python/layers/test_maxpool.py

@@ -26,7 +26,7 @@ def test_maxpool(self):
         # NOTE: take note of use of {{ }}
         LANG = """
         def maxpool(float(B, C, H, W) input) -> (output) {{
-            output(b, c, h, w) max= input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+            output(b, c, h, w) max=! input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
         }}
         """
         maxpool = tc.define(LANG, name="maxpool", constants={"sH":1, "sW":1, "kH":2, "kW":2})

test_python/test_scalar_tc.py

@@ -25,7 +25,7 @@ def test_avgpool_option1(self):
         # NOTE: take note of use of {{ }} below for handling TC with scalars
         LANG = """
         def avgpool(float(B, C, H, W) input) -> (output) {{
-            output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+            output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
         }}
         """
         avgpool = tc.define(LANG, name="avgpool", constants={"sH":1, "sW":1, "kH":2, "kW":2})
@@ -36,7 +36,7 @@ def test_avgpool_option2(self):
         # NOTE: take note of use of {{ }}
         LANG="""
         def avgpool(float(B, C, H, W) input) -> (output) {{
-            output(b, c, h, w) += input(b, c, h * {sh} + kh, w * {sw} + kw) where kh = [0, {kH}[, kw = [0, {kW}[
+            output(b, c, h, w) +=! input(b, c, h * {sh} + kh, w * {sw} + kw) / ({kH} * {kW}) where kh = [0, {kH}[, kw = [0, {kW}[
         }}
         """
         sH, sW, kH, kW = 1, 1, 2, 2
@@ -51,7 +51,7 @@ def test_avgpool_option3(self):
         import re
         LANG="""
         def avgpool(float(B, C, H, W) input) -> (output) {
-            output(b, c, h, w) += input(b, c, h * <sh> + kh, w * <sw> + kw) where kh in 0:<kH>, kw in 0:<kW>
+            output(b, c, h, w) +=! input(b, c, h * <sh> + kh, w * <sw> + kw) / (<kH> * <kW>) where kh in 0:<kH>, kw in 0:<kW>
         }
         """
         sH, sW, kH, kW = 1, 1, 2, 2

test_python/test_tc_torch.py

@@ -102,7 +102,7 @@ def test_avgpool(self):
         # NOTE: take note of use of {{ }}
         LANG = """
         def avgpool(float(B, C, H, W) input) -> (output) {{
-            output(b, c, h, w) += input(b, c, h * {sH} + kh, w * {sW} + kw) where kh in 0:{kH}, kw in 0:{kW}
+            output(b, c, h, w) +=! input(b, c, h * {sH} + kh, w * {sW} + kw) / ({kH} * {kW}) where kh in 0:{kH}, kw in 0:{kW}
         }}
         """
         avgpool = tc.define(LANG, name="avgpool", constants={"sH":1, "sW":1, "kH":2, "kW":2})