[PYTHON] Renamed triton.core -> triton.language (#92)

python/tutorials/01-vector-add.py

@@ -13,6 +13,7 @@ In this tutorial, you will write a simple vector addition using Triton and learn
 # --------------------------
 
 import torch
+import triton.language as tl
 import triton
 
 
@@ -24,19 +25,19 @@ def _add(
     N,  # Size of the vector
     **meta  # Optional meta-parameters for the kernel
 ):
-    pid = triton.program_id(0)
+    pid = tl.program_id(0)
     # Create an offset for the blocks of pointers to be
     # processed by this program instance
-    offsets = pid * meta['BLOCK'] + triton.arange(0, meta['BLOCK'])
+    offsets = pid * meta['BLOCK'] + tl.arange(0, meta['BLOCK'])
     # Create a mask to guard memory operations against
     # out-of-bounds accesses
     mask = offsets < N
     # Load x
-    x = triton.load(X + offsets, mask=mask)
-    y = triton.load(Y + offsets, mask=mask)
+    x = tl.load(X + offsets, mask=mask)
+    y = tl.load(Y + offsets, mask=mask)
     # Write back x + y
     z = x + y
-    triton.store(Z + offsets, z)
+    tl.store(Z + offsets, z)
 
 
 # %%
@@ -89,9 +90,9 @@ print(f'The maximum difference between torch and triton is ' f'{torch.max(torch.
         x_names=['size'],  # argument names to use as an x-axis for the plot
         x_vals=[2**i for i in range(12, 28, 1)],  # different possible values for `x_name`
         x_log=True,  # x axis is logarithmic
-        y_name='provider',  # argument name whose value corresponds to a different line in the plot
-        y_vals=['torch', 'triton'],  # possible keys for `y_name`
-        y_lines=["Torch", "Triton"],  # label name for the lines
+        line_arg='provider',  # argument name whose value corresponds to a different line in the plot
+        line_vals=['torch', 'triton'],  # possible values for `line_arg`
+        line_names=["Torch", "Triton"],  # label name for the lines
         ylabel="GB/s",  # label name for the y-axis
         plot_name="vector-add-performance",  # name for the plot. Used also as a file name for saving the plot.
         args={}  # values for function arguments not in `x_names` and `y_name`