add xlib.avecl

xlib/avecl/_internal/op/gaussian_blur.py

@@ -0,0 +1,39 @@
+import numpy as np
+
+from ..Tensor import Tensor
+from .depthwise_conv2D import depthwise_conv2D
+
+
+def gaussian_blur (input_t : Tensor, sigma, dtype=None) -> Tensor:
+    """
+    arguments
+
+        input_t     Tensor(...,H,W)
+
+        sigma       float
+
+
+    """
+    if sigma <= 0.0:
+        return input_t.copy() #TODO
+
+    device = input_t.get_device()
+
+    key = (gaussian_blur, sigma)
+    kernel_t = device.get_cached_data(key)
+    if kernel_t is None:
+        kernel_t = Tensor.from_value( _make_gaussian_kernel(sigma, np.float32), device=device )
+        device.set_cached_data(key, kernel_t)
+
+    output_t = depthwise_conv2D(input_t, kernel_t, dtype=dtype)
+    return output_t
+
+def _make_gaussian_kernel(sigma : float, dtype):
+    kernel_size = max(3, int(2 * 2 * sigma))
+    if kernel_size % 2 == 0:
+        kernel_size += 1
+    mean = np.floor(0.5 * kernel_size)
+    kernel_1d = np.array([ np.exp(-(float(x) - float(mean)) ** 2 / (2 * sigma ** 2)) for x in range(kernel_size)])
+    np_kernel = np.outer(kernel_1d, kernel_1d)
+    kernel = np_kernel / np.sum(np_kernel)
+    return kernel.astype(dtype)