Windows raw string fix (#10998)
Summary:
Breaking this out of https://github.com/pytorch/pytorch/pull/8338
mingzhe09088's fix of the docstrings for Windows builds. Unfortunately some versions of Windows seem to try and parse the `#` inside the string as a pre-processor declaration. We might need to change this to something else later, but want to get this landed first.
cc mingzhe09088 Yangqing
Pull Request resolved: https://github.com/pytorch/pytorch/pull/10998
Reviewed By: mingzhe09088
Differential Revision: D9557480
Pulled By: orionr
fbshipit-source-id: c6a6237c27b7cf35c81133fd9faefead675a9f59
diff --git a/caffe2/operators/concat_split_op.cc b/caffe2/operators/concat_split_op.cc
index a8f4c91..3125602 100644
--- a/caffe2/operators/concat_split_op.cc
+++ b/caffe2/operators/concat_split_op.cc
@@ -311,8 +311,8 @@
axis=3
)
-workspace.FeedBlob("X1", np.random.randint(10, size=(1, 1, 5, 5))) # NCHW
-workspace.FeedBlob("X2", np.random.randint(10, size=(1, 1, 5, 5))) # NCHW
+workspace.FeedBlob("X1", np.random.randint(10, size=(1, 1, 5, 5))) // NCHW
+workspace.FeedBlob("X2", np.random.randint(10, size=(1, 1, 5, 5))) // NCHW
print("X1:", workspace.FetchBlob("X1"))
print("X2:", workspace.FetchBlob("X2"))
workspace.RunOperatorOnce(op)
diff --git a/caffe2/operators/conv_op.cc b/caffe2/operators/conv_op.cc
index 082c94f..30fb79d 100644
--- a/caffe2/operators/conv_op.cc
+++ b/caffe2/operators/conv_op.cc
@@ -42,24 +42,24 @@
stride=2
)
-# Create X: (N,C,H,W)
+// Create X: (N,C,H,W)
data = np.random.randn(1,1,8,8).astype(np.float32)
print("Data shape: ",data.shape)
-# Create W: (M,C,Kh,Kw)
+// Create W: (M,C,Kh,Kw)
filters = np.random.randn(3,1,5,5).astype(np.float32)
print("Filter shape: ",filters.shape)
-# Create b: M
+// Create b: M
bias = np.array([1.,1.,1.]).astype(np.float32)
print("Bias shape: ",bias.shape)
-# Put the inputs into the workspace
+// Put the inputs into the workspace
workspace.FeedBlob("X", data)
workspace.FeedBlob("filter", filters)
workspace.FeedBlob("bias", bias)
-# Run the operator
+// Run the operator
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
diff --git a/caffe2/operators/conv_transpose_op.cc b/caffe2/operators/conv_transpose_op.cc
index 57ec02b..7de16af 100644
--- a/caffe2/operators/conv_transpose_op.cc
+++ b/caffe2/operators/conv_transpose_op.cc
@@ -44,24 +44,24 @@
strides=[2,2]
)
-# Create X: (N,C,H,W)
+// Create X: (N,C,H,W)
data = np.random.randn(2,3,5,5).astype(np.float32)
print("Data shape: ",data.shape)
-# Create filter: (M,C,Kh,Kw)
+// Create filter: (M,C,Kh,Kw)
filters = np.random.randn(3,1,2,2).astype(np.float32)
print("Filter shape: ",filters.shape)
-# Create b: M
+// Create b: M
bias = np.array([1.]).astype(np.float32)
print("Bias shape: ",bias.shape)
-# Put the inputs into the workspace
+// Put the inputs into the workspace
workspace.FeedBlob("X", data)
workspace.FeedBlob("filter", filters)
workspace.FeedBlob("bias", bias)
-# Run the operator
+// Run the operator
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
diff --git a/caffe2/operators/counter_ops.cc b/caffe2/operators/counter_ops.cc
index 15cdab5..50e4b94 100644
--- a/caffe2/operators/counter_ops.cc
+++ b/caffe2/operators/counter_ops.cc
@@ -58,22 +58,22 @@
)
-# Create counter
+// Create counter
workspace.RunOperatorOnce(createcounter_op)
print("'counter' pointer:", workspace.FetchBlob("counter"))
-# Retrieve initial counter value
+// Retrieve initial counter value
workspace.RunOperatorOnce(retrievecount_op)
print("Initial 'count':", workspace.FetchBlob("count"))
-# Check if counter is done
+// Check if counter is done
workspace.RunOperatorOnce(checkcounterdone_op)
print("Initial 'done' value:", workspace.FetchBlob("done"))
-# Test CountUp operator
+// Test CountUp operator
print("\nTesting CountUp operator...")
for i in range(5):
workspace.RunOperatorOnce(countup_op)
@@ -83,7 +83,7 @@
print("'count' value after CountUp test:", workspace.FetchBlob("count"))
-# Test CountDown operator
+// Test CountDown operator
print("\nTesting CountDown operator...")
for i in range(11):
workspace.RunOperatorOnce(countdown_op)
diff --git a/caffe2/operators/cross_entropy_op.cc b/caffe2/operators/cross_entropy_op.cc
index 584b7ab..0473e7d4 100644
--- a/caffe2/operators/cross_entropy_op.cc
+++ b/caffe2/operators/cross_entropy_op.cc
@@ -401,22 +401,22 @@
["Y"]
)
-# Create X: Sample softmax output for 5-class model
+// Create X: Sample softmax output for 5-class model
X = np.array([[.01, .05, .02, .02, .9],[.03, .1, .42, .05, .4]])
print("X:\n",X)
-# Create label: Sample 1-hot ground truth label vectors
+// Create label: Sample 1-hot ground truth label vectors
label = np.array([4,2])
print("label:\n",label)
-# Feed X & label into workspace
+// Feed X & label into workspace
workspace.FeedBlob("X", X.astype(np.float32))
workspace.FeedBlob("label", label.astype(np.int32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Y:\n", workspace.FetchBlob("Y"))
```
@@ -635,22 +635,22 @@
["Y"]
)
-# Create X: Sample softmax output for 5-class model
+// Create X: Sample softmax output for 5-class model
X = np.array([[.01, .05, .02, .02, .9],[.03, .1, .42, .05, .4]])
print("X:\n",X)
-# Create label: Sample 1-hot ground truth label vectors
+// Create label: Sample 1-hot ground truth label vectors
label = np.array([[0.,0.,0.,0.,1.],[0.,0.,1.,0.,0.]])
print("label:\n",label)
-# Feed X & label into workspace
+// Feed X & label into workspace
workspace.FeedBlob("X", X.astype(np.float32))
workspace.FeedBlob("label", label.astype(np.float32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Y:\n", workspace.FetchBlob("Y"))
```
diff --git a/caffe2/operators/distance_op.cc b/caffe2/operators/distance_op.cc
index d9abfa0..9a38a4a7 100644
--- a/caffe2/operators/distance_op.cc
+++ b/caffe2/operators/distance_op.cc
@@ -437,22 +437,22 @@
["Z"]
)
-# Create X
+// Create X
X = 5*np.ones((1, 4))
print("X:\n",X)
-# Create Y
+// Create Y
Y = np.ones((1, 4))
print("Y:\n",Y)
-# Feed X & Y into workspace
+// Feed X & Y into workspace
workspace.FeedBlob("X", X.astype(np.float32))
workspace.FeedBlob("Y", Y.astype(np.float32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Z:\n", workspace.FetchBlob("Z"))
```
@@ -645,22 +645,22 @@
["Z"]
)
-# Create X
+// Create X
X = np.random.randn(3, 3)
print("X:\n",X)
-# Create Y
+// Create Y
Y = np.random.randn(3, 3)
print("Y:\n",Y)
-# Feed X & Y into workspace
+// Feed X & Y into workspace
workspace.FeedBlob("X", X.astype(np.float32))
workspace.FeedBlob("Y", Y.astype(np.float32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Z:\n", workspace.FetchBlob("Z"))
```
diff --git a/caffe2/operators/elementwise_linear_op.cc b/caffe2/operators/elementwise_linear_op.cc
index d68bfbc..371aae7 100644
--- a/caffe2/operators/elementwise_linear_op.cc
+++ b/caffe2/operators/elementwise_linear_op.cc
@@ -112,28 +112,28 @@
["Y"]
)
-# Create X
+// Create X
X = np.array([[1,2,3,4,5],[6,8,9,16,10]])
print("X:\n",X)
-# Create w
+// Create w
w = np.array([1,1/2.,1/3.,1/4.,1/5.])
print("w:\n",w)
-# Create b
+// Create b
b = np.array([1.,1.,1.,1.,1.])
print("b:\n",b)
-# Feed X & w & b into workspace
+// Feed X & w & b into workspace
workspace.FeedBlob("X", X.astype(np.float32))
workspace.FeedBlob("w", w.astype(np.float32))
workspace.FeedBlob("b", b.astype(np.float32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Y:\n", workspace.FetchBlob("Y"))
```
diff --git a/caffe2/operators/elementwise_logical_ops.cc b/caffe2/operators/elementwise_logical_ops.cc
index 5ddd457..0e2da56 100644
--- a/caffe2/operators/elementwise_logical_ops.cc
+++ b/caffe2/operators/elementwise_logical_ops.cc
@@ -63,7 +63,7 @@
value=[0,2,4,6,8],
)
-# Use a not-empty tensor
+// Use a not-empty tensor
workspace.FeedBlob("X", np.array([0,1,2,3,4,5,6,7,8]).astype(np.int32))
print("X:\n", workspace.FetchBlob("X"))
@@ -75,7 +75,7 @@
**Result**
```
-# value=[0,2,4,6,8]
+// value=[0,2,4,6,8]
X:
[0 1 2 3 4 5 6 7 8]
diff --git a/caffe2/operators/elementwise_sum_op.cc b/caffe2/operators/elementwise_sum_op.cc
index 861f4f1..dee3671 100644
--- a/caffe2/operators/elementwise_sum_op.cc
+++ b/caffe2/operators/elementwise_sum_op.cc
@@ -86,7 +86,7 @@
op = core.CreateOperator(
"Sum",
["A", "B"],
- ["A"], # inplace
+ ["A"], // inplace
)
workspace.FeedBlob("A", np.array([[1,2,5],[8,3,4]]).astype(np.float32))
diff --git a/caffe2/operators/filler_op.cc b/caffe2/operators/filler_op.cc
index ff3eac2..c5a121e 100644
--- a/caffe2/operators/filler_op.cc
+++ b/caffe2/operators/filler_op.cc
@@ -298,11 +298,11 @@
input_as_shape=1
)
-# Test arg-based op
+// Test arg-based op
workspace.RunOperatorOnce(op_1)
print("output (op_1):\n", workspace.FetchBlob("output"))
-# Test input-based op
+// Test input-based op
workspace.ResetWorkspace()
workspace.FeedBlob("shape", np.array([5,5]))
workspace.FeedBlob("min", np.array(13.8, dtype=np.float32))
@@ -389,11 +389,11 @@
input_as_shape=1
)
-# Test arg-based op
+// Test arg-based op
workspace.RunOperatorOnce(op_1)
print("output (op_1):\n", workspace.FetchBlob("output"))
-# Test input-based op
+// Test input-based op
workspace.ResetWorkspace()
workspace.FeedBlob("shape", np.array([5,5]))
workspace.FeedBlob("min", np.array(13, dtype=np.int32))
diff --git a/caffe2/operators/fully_connected_op.cc b/caffe2/operators/fully_connected_op.cc
index 6fe95ee..e14fec6 100644
--- a/caffe2/operators/fully_connected_op.cc
+++ b/caffe2/operators/fully_connected_op.cc
@@ -182,9 +182,9 @@
```
-# In this example, our batch size is 1 (M=1), the input observation will have
-# 6 features (K=6), and the layer will have one hidden node (N=1). The
-# expected output is Y=7.
+// In this example, our batch size is 1 (M=1), the input observation will have
+// 6 features (K=6), and the layer will have one hidden node (N=1). The
+// expected output is Y=7.
workspace.ResetWorkspace()
op = core.CreateOperator(
@@ -193,23 +193,23 @@
["Y"]
)
-# Create X: MxK
+// Create X: MxK
data = np.array([1,2,3,4,5,6]).astype(np.float32)
data = data[np.newaxis,:]
-# Create W: NxK
+// Create W: NxK
weights = np.array(np.array([1,1/2.,1/3.,1/4.,1/5.,1/6.])).astype(np.float32)
weights = weights[np.newaxis,:]
-# Create b: N
+// Create b: N
bias = np.array([1.]).astype(np.float32)
-# Put the inputs into the workspace
+// Put the inputs into the workspace
workspace.FeedBlob("X", data)
workspace.FeedBlob("W", weights)
workspace.FeedBlob("b", bias)
-# Run the operator
+// Run the operator
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
diff --git a/caffe2/operators/gather_op.cc b/caffe2/operators/gather_op.cc
index cee268d..34c42bf 100644
--- a/caffe2/operators/gather_op.cc
+++ b/caffe2/operators/gather_op.cc
@@ -37,7 +37,7 @@
inds = np.array([[0, 1],[1, 2]])
print("INDICES:\n",inds)
-# Feed X into workspace
+// Feed X into workspace
workspace.FeedBlob("DATA", data.astype(np.float32))
workspace.FeedBlob("INDICES", inds.astype(np.int32))
diff --git a/caffe2/operators/local_response_normalization_op.cc b/caffe2/operators/local_response_normalization_op.cc
index 1cba60e..81499b4 100644
--- a/caffe2/operators/local_response_normalization_op.cc
+++ b/caffe2/operators/local_response_normalization_op.cc
@@ -342,7 +342,7 @@
order="NHWC"
)
-workspace.FeedBlob("X", np.random.randn(1, 6, 6, 1).astype(np.float32)) # NCHW
+workspace.FeedBlob("X", np.random.randn(1, 6, 6, 1).astype(np.float32)) // NCHW
print("X:\n", workspace.FetchBlob("X"), "\n")
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
diff --git a/caffe2/operators/lp_pool_op.cc b/caffe2/operators/lp_pool_op.cc
index f877786..f39aaaa 100644
--- a/caffe2/operators/lp_pool_op.cc
+++ b/caffe2/operators/lp_pool_op.cc
@@ -258,7 +258,7 @@
p=2.0
)
-workspace.FeedBlob("X", np.random.randn(1, 1, 6, 6).astype(np.float32)) # NCHW
+workspace.FeedBlob("X", np.random.randn(1, 1, 6, 6).astype(np.float32)) // NCHW
print("X:\n", workspace.FetchBlob("X"), "\n")
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
diff --git a/caffe2/operators/lpnorm_op.cc b/caffe2/operators/lpnorm_op.cc
index 6af404d..79c35cd 100644
--- a/caffe2/operators/lpnorm_op.cc
+++ b/caffe2/operators/lpnorm_op.cc
@@ -100,7 +100,7 @@
X = np.array([5., 2.])
print("X:\n",X)
-# Feed X into workspace
+// Feed X into workspace
workspace.FeedBlob("X", X.astype(np.float32))
workspace.RunOperatorOnce(op)
diff --git a/caffe2/operators/pool_op.cc b/caffe2/operators/pool_op.cc
index eca7978..87d67b1 100644
--- a/caffe2/operators/pool_op.cc
+++ b/caffe2/operators/pool_op.cc
@@ -764,7 +764,7 @@
stride=2,
)
-workspace.FeedBlob("X", np.random.randn(1, 1, 6, 6).astype(np.float32)) # NCHW
+workspace.FeedBlob("X", np.random.randn(1, 1, 6, 6).astype(np.float32)) // NCHW
print("X:\n", workspace.FetchBlob("X"), "\n")
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
@@ -832,7 +832,7 @@
stride=2,
)
-workspace.FeedBlob("X", np.random.randn(1, 1, 6, 6).astype(np.float32)) # NCHW
+workspace.FeedBlob("X", np.random.randn(1, 1, 6, 6).astype(np.float32)) // NCHW
print("X:\n", workspace.FetchBlob("X"), "\n")
workspace.RunOperatorOnce(op)
print("Y:\n", workspace.FetchBlob("Y"))
diff --git a/caffe2/operators/reduction_ops.cc b/caffe2/operators/reduction_ops.cc
index 0d01d50..95f15b5 100644
--- a/caffe2/operators/reduction_ops.cc
+++ b/caffe2/operators/reduction_ops.cc
@@ -139,17 +139,17 @@
["Y"]
)
-# Create X, simulating a batch of 2, 4x4 matricies
+// Create X, simulating a batch of 2, 4x4 matricies
X = np.random.randint(0,high=20,size=(2,4,4))
print("X:\n",X)
-# Feed X into workspace
+// Feed X into workspace
workspace.FeedBlob("X", X.astype(np.float32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Y:\n", workspace.FetchBlob("Y"))
```
@@ -226,17 +226,17 @@
["Y"]
)
-# Create X, simulating a batch of 2, 4x4 matricies
+// Create X, simulating a batch of 2, 4x4 matricies
X = np.random.randint(0,high=20,size=(2,4,4))
print("X:\n",X)
-# Feed X into workspace
+// Feed X into workspace
workspace.FeedBlob("X", X.astype(np.float32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Y:\n", workspace.FetchBlob("Y"))
```
diff --git a/caffe2/operators/relu_op.cc b/caffe2/operators/relu_op.cc
index 0320524..0f1abd8 100644
--- a/caffe2/operators/relu_op.cc
+++ b/caffe2/operators/relu_op.cc
@@ -105,7 +105,7 @@
["Y"]
)
-workspace.FeedBlob("X", np.random.randn(4, 4).astype(np.float32)) # NCHW
+workspace.FeedBlob("X", np.random.randn(4, 4).astype(np.float32)) // NCHW
print("X:\n", workspace.FetchBlob("X"), "\n")
workspace.RunOperatorOnce(op)
diff --git a/caffe2/operators/sparse_to_dense_mask_op.cc b/caffe2/operators/sparse_to_dense_mask_op.cc
index bea0b43..d968112 100644
--- a/caffe2/operators/sparse_to_dense_mask_op.cc
+++ b/caffe2/operators/sparse_to_dense_mask_op.cc
@@ -48,8 +48,8 @@
corresponds to each id provided in mask argument. Missing values are filled with
the value of `default_value`. After running this op:
- output[j, :] = values[i] # where mask[j] == indices[i]
- output[j, ...] = default_value # when mask[j] doesn't appear in indices
+ output[j, :] = values[i] // where mask[j] == indices[i]
+ output[j, ...] = default_value // when mask[j] doesn't appear in indices
If `lengths` is provided and not empty, and extra "batch" dimension is prepended
to the output.
diff --git a/caffe2/operators/sparse_to_dense_op.cc b/caffe2/operators/sparse_to_dense_op.cc
index 4f6a497..0c9519e 100644
--- a/caffe2/operators/sparse_to_dense_op.cc
+++ b/caffe2/operators/sparse_to_dense_op.cc
@@ -23,7 +23,7 @@
After running this op:
- output[indices[i], :] += values[i] # sum over all indices[i] equal to the index
+ output[indices[i], :] += values[i] // sum over all indices[i] equal to the index
output[j, ...] = 0 if j not in indices
)DOC")
.Input(0, "indices", "1-D int32/int64 tensor of concatenated ids of data")
diff --git a/caffe2/operators/stats_ops.cc b/caffe2/operators/stats_ops.cc
index 508dd1a..d07f9ca 100644
--- a/caffe2/operators/stats_ops.cc
+++ b/caffe2/operators/stats_ops.cc
@@ -290,7 +290,7 @@
["nanos"]
)
-# Test TimerBegin/TimerGet/TimerEnd
+// Test TimerBegin/TimerGet/TimerEnd
workspace.RunOperatorOnce(timerbegin_op)
print("timer:", workspace.FetchBlob("timer"))
workspace.RunOperatorOnce(timerget_op)
@@ -298,7 +298,7 @@
workspace.RunOperatorOnce(timerend_op)
-# Test TimerBegin/TimerGetAndEnd
+// Test TimerBegin/TimerGetAndEnd
workspace.RunOperatorOnce(timerbegin_op)
print("timer:", workspace.FetchBlob("timer"))
workspace.RunOperatorOnce(timergetandend_op)
diff --git a/caffe2/operators/utility_ops.cc b/caffe2/operators/utility_ops.cc
index cc7c037..eb77197 100644
--- a/caffe2/operators/utility_ops.cc
+++ b/caffe2/operators/utility_ops.cc
@@ -103,17 +103,17 @@
["Y"]
)
-# Create X: Sample softmax output for 5-class model
+// Create X: Sample softmax output for 5-class model
X = np.array([2,2,2,2,2,2,2,2,2,2])
print("X:\n",X)
-# Feed X into workspace
+// Feed X into workspace
workspace.FeedBlob("X", X.astype(np.int32))
-# Run op
+// Run op
workspace.RunOperatorOnce(op)
-# Collect Output
+// Collect Output
print("Y:\n", workspace.FetchBlob("Y"))
```
@@ -508,14 +508,14 @@
["has_elements"],
)
-# Use a not-empty tensor
+// Use a not-empty tensor
workspace.FeedBlob("tensor", np.random.randn(2, 2).astype(np.float32))
print("tensor:\n", workspace.FetchBlob("tensor"))
workspace.RunOperatorOnce(op)
print("has_elements: ", workspace.FetchBlob("has_elements"),"\n")
-# Use an empty tensor
+// Use an empty tensor
workspace.FeedBlob("tensor", np.empty(0))
print("tensor:\n", workspace.FetchBlob("tensor"))
