Change 1d,2d,... to 1D,2D,... (#997)

CHANGELOG.md

@@ -17,7 +17,7 @@ None
 - Support for 3D grouped convolution on RDNA 3 GPUs (#935, #950, #985)
 - Grouped convolution support for small K and C (#822 #879 #897)
 - Support for NHWGC (2D and 3D) grouped convolution backward weight (#769 #804)
-- Support for bf16/f32/f16 and NHWGC (2D and 3d) grouped convolution backward data (#757 #799)
+- Support for bf16/f32/f16 and NHWGC (2D and 3D) grouped convolution backward data (#757 #799)
 - Support for Batched Gemm DL (#732)
 
 ### Changes

example/12_reduce/README.md

@@ -2,7 +2,7 @@
 
 ## Run ```example_reduce_blockwise```
 ```bash
-# -D <xxx> : input 3d/4d/5d tensor lengths
+# -D <xxx> : input 3D/4D/5D tensor lengths
 # -R <xxx> : reduce dimension ids
 # -v <x> :   verification (0=no, 1=yes)
 #arg1: data type (0: fp16, 1: fp32, 3: int8, 5: bp16, 6: fp64, 7: int4)
@@ -22,7 +22,7 @@ Perf: 0.238063 ms, 264.285 GB/s, DeviceReduceBlockWise<256,M_C4_S1,K_C64_S1,InSr
 
 ## Run ```example_reduce_multiblock_atomic_add```
 ```bash
-# -D <xxx> : input 3d/4d/5d tensor lengths
+# -D <xxx> : input 3D/4D/5D tensor lengths
 # -R <xxx> : reduce dimension ids
 # -v <x> :   verification (0=no, 1=yes)
 #arg1: data type (0: fp32, 1: fp64)

example/30_grouped_conv_fwd_multiple_d/README.md

@@ -4,7 +4,7 @@ arg1: verification (0=no, 1=yes)
 arg2: initialization (0=no init, 1=integer value, 2=decimal value)
 arg3: time kernel (0=no, 1=yes)
 Following arguments (depending on number of spatial dims):
- Number of spatial dimensions (1=Conv1d, 2=Conv2d, 3=Conv3d)
+ Number of spatial dimensions (1=Conv1D, 2=Conv2D, 3=Conv3D)
  G, N, K, C,
  <filter spatial dimensions>, (ie Y, X for 2D)
  <input image spatial dimensions>, (ie Hi, Wi for 2D)

profiler/README.md

@@ -22,7 +22,7 @@ c_m_n: dim 2, lengths {3840, 4096}, strides {4096, 1}
 Best Perf: 1.1933 ms, 107.977 TFlops, 79.0848 GB/s
 ```
 
-## Profile 2d forward convolution kernels
+## Profile 2D forward convolution kernels
 ```bash
 #arg1: tensor operation (conv=Convolution)
 #arg2: data type (0=fp32, 1=fp16)
@@ -115,7 +115,7 @@ Best Perf: 58.0306 ms, 37.8942 TFlops, 27.7545 GB/s
 # arg6: print tensor value (0: no; 1: yes)
 # arg7: time kernel (0: no, 1: yes)
 # Following arguments (depending on number of spatial dims):
-#  Number of spatial dimensions (1=Conv1d, 2=Conv2d, 3=Conv3d)
+#  Number of spatial dimensions (1=Conv1D, 2=Conv2D, 3=Conv3D)
 #  G, N, K, C, 
 #  <filter spatial dimensions>, (ie Y, X for 2D)
 #  <input image spatial dimensions>, (ie Hi, Wi for 2D)
@@ -158,7 +158,7 @@ GB/s: 127.947
 # arg6: print tensor value (0: no; 1: yes)
 # arg7: time kernel (0: no, 1: yes)
 # Following arguments (depending on number of spatial dims):
-#  Number of spatial dimensions (1=Conv1d, 2=Conv2d, 3=Conv3d)
+#  Number of spatial dimensions (1=Conv1D, 2=Conv2D, 3=Conv3D)
 #  G, N, K, C, 
 #  <filter spatial dimensions>, (ie Y, X for 2D)
 #  <input image spatial dimensions>, (ie Hi, Wi for 2D)
@@ -201,7 +201,7 @@ Note: This kernel use atomic add, this will cause output buffer to be accumulate
 # arg7: time kernel (0: no, 1: yes)
 # arg8: operation type (0: ImageToColumn, 1: ColumnToImage)
 # Following arguments (depending on number of spatial dims):
-#  Number of spatial dimensions (1=Conv1d, 2=Conv2d, 3=Conv3d)
+#  Number of spatial dimensions (1=Conv1D, 2=Conv2D, 3=Conv3D)
 #  G, N, K, C, 
 #  <filter spatial dimensions>, (ie Y, X for 2D)
 #  <input image spatial dimensions>, (ie Hi, Wi for 2D)