chore: import upstream snapshot with attribution

2026-07-13 12:45:52 +08:00
commit 7217e2df3b
2092 changed files with 479877 additions and 0 deletions
@@ -0,0 +1,68 @@
+from ggml import ffi, lib
+from ggml.utils import init, numpy, copy
+import numpy as np
+from math import pi, cos, sin, ceil
+
+import matplotlib.pyplot as plt
+
+ctx = init(mem_size=100*1024*1024) # Will be auto-GC'd
+n = 256
+
+orig = np.array([
+    [
+        cos(j * 2 * pi / n) * (sin(i * 2 * pi / n))
+        for j in range(n)
+    ]
+    for i in range(n)
+], np.float32)
+orig_tensor = lib.ggml_new_tensor_2d(ctx, lib.GGML_TYPE_F32, n, n)
+copy(orig, orig_tensor)
+
+quants = [
+    type for type in range(lib.GGML_TYPE_COUNT)
+    if lib.ggml_is_quantized(type) and
+       type not in [lib.GGML_TYPE_Q8_1, lib.GGML_TYPE_Q8_K] # Apparently not supported
+]
+# quants = [lib.GGML_TYPE_Q2_K] # Test a single one
+
+def get_name(type):
+    name = lib.ggml_type_name(type)
+    return ffi.string(name).decode('utf-8') if name else '?'
+
+quants.sort(key=get_name)
+quants.insert(0, None)
+print(quants)
+
+ncols=4
+nrows = ceil(len(quants) / ncols)
+
+plt.figure(figsize=(ncols * 5, nrows * 5), layout='tight')
+
+for i, type in enumerate(quants):
+    plt.subplot(nrows, ncols, i + 1)
+    try:
+        if type == None:
+            plt.title('Original')
+            plt.imshow(orig)
+        else:
+            quantized_tensor = lib.ggml_new_tensor_2d(ctx, type, n, n)
+            copy(orig_tensor, quantized_tensor)
+            quantized = numpy(quantized_tensor, allow_copy=True)
+            d = quantized - orig
+            results = {
+                "l2": np.linalg.norm(d, 2),
+                "linf": np.linalg.norm(d, np.inf),
+                "compression":
+                    round(lib.ggml_nbytes(orig_tensor) /
+                          lib.ggml_nbytes(quantized_tensor), 1)
+            }
+            name = get_name(type)
+            print(f'{name}: {results}')
+
+            plt.title(f'{name} ({results["compression"]}x smaller)')
+            plt.imshow(quantized, interpolation='nearest')
+        
+    except Exception as e:
+        print(f'Error: {e}')
+
+plt.show()