[TOPI] Add GPU SSD (#1397)

topi/python/topi/cuda/__init__.py

@@ -15,6 +15,8 @@ from .dense import dense_cuda, schedule_dense
 from .pooling import schedule_pool, schedule_global_pool
 from .conv2d_transpose_nchw import schedule_conv2d_transpose_nchw
 from .extern import schedule_extern
-from .vision import schedule_region
-from .vision import schedule_reorg
 from .nn import schedule_lrn, schedule_l2_normalize
+from .vision import *
+from . import ssd
+from .ssd import *
+from .nms import *

topi/python/topi/cuda/ssd/__init__.py

+# pylint: disable=wildcard-import
+"""VISION network operators"""
+from __future__ import absolute_import as _abs
+
+from .multibox import *

topi/python/topi/cuda/vision.py

-# pylint: disable=invalid-name, unused-variable, unused-argument
+# pylint: disable=invalid-name, unused-variable, unused-argument, no-member
 """Schedule for vision operators"""
 from __future__ import absolute_import as _abs
 import tvm
 from .. import generic
 from .. import cpp
+from .. import tag
+
+def _default_schedule(outs):
+    """Default schedule for gpu."""
+    target = tvm.target.current_target()
+    outs = [outs] if isinstance(outs, tvm.tensor.Tensor) else outs
+    s = tvm.create_schedule([x.op for x in outs])
+    def traverse(op):
+        """inline all one-to-one-mapping operators except the last stage (output)"""
+        if "nms" in op.tag:
+            sort = op.input_tensors[1]
+            score = s[sort].op.input_tensors[0]
+            fused = s[score].fuse(*s[score].op.axis)
+            num_thread = tvm.target.current_target(allow_none=False).max_num_threads
+            bx, tx = s[score].split(fused, factor=num_thread)
+            s[score].bind(bx, tvm.thread_axis("blockIdx.x"))
+            s[score].bind(tx, tvm.thread_axis("threadIdx.x"))
+        if tag.is_broadcast(op.tag):
+            if op not in s.outputs:
+                s[op].compute_inline()
+            else:
+                x = op.output(0)
+                fused = s[x].fuse(*s[x].op.axis)
+                num_thread = tvm.target.current_target(allow_none=False).max_num_threads
+                bx, tx = s[x].split(fused, factor=num_thread)
+                s[x].bind(bx, tvm.thread_axis("blockIdx.x"))
+                s[x].bind(tx, tvm.thread_axis("threadIdx.x"))
+            for tensor in op.input_tensors:
+                if tensor.op.input_tensors:
+                    traverse(tensor.op)
+
+    traverse(outs[0].op)
+    return s
 
 @generic.schedule_reorg.register(["cuda", "gpu"])
 def schedule_reorg(outs):
@@ -41,8 +74,25 @@ def schedule_region(outs):
     cpp_target = cpp.TEST_create_target(target.target_name)
     return cpp.cuda.schedule_region(cpp_target, outs)
 
+@generic.schedule_nms.register(["cuda", "gpu"])
+def schedule_nms(outs):
+    """Schedule for non-maximum suppression
+
+    Parameters
+    ----------
+    outs: Array of Tensor
+      The computation graph description of nms
+      in the format of an array of tensors.
+
+    Returns
+    -------
+    s: Schedule
+      The computation schedule for the op.
+    """
+    return _default_schedule(outs)
+
 @generic.schedule_multibox_prior.register(["cuda", "gpu"])
-def schedule_multibox_prior(out):
+def schedule_multibox_prior(outs):
     """Schedule for multibox_prior operator.
 
     Parameters
@@ -56,10 +106,28 @@ def schedule_multibox_prior(out):
     s: Schedule
         The computation schedule for multibox_prior.
     """
-    raise RuntimeError("Currently multibox_prior only supports CPU.")
+    return _default_schedule(outs)
+
+@generic.schedule_multibox_transform_loc.register(["cuda", "gpu"])
+def schedule_multibox_transform_loc(outs):
+    """Schedule for multibox_transform_loc
+
+    Parameters
+    ----------
+    outs: Array of Tensor
+      The computation graph description of
+      multibox_transform_loc in the format
+      of an array of tensors.
+
+    Returns
+    -------
+    s: Schedule
+      The computation schedule for the op.
+    """
+    return _default_schedule(outs)
 
 @generic.schedule_multibox_detection.register(["cuda", "gpu"])
-def schedule_multibox_detection(out):
+def schedule_multibox_detection(outs):
     """Schedule for multibox_detection operator.
 
     Parameters
@@ -73,4 +141,4 @@ def schedule_multibox_detection(out):
     s: Schedule
         The computation schedule for multibox_detection.
     """
-    raise RuntimeError("Currently multibox_detection only supports CPU.")
+    return _default_schedule(outs)

topi/tests/python/test_topi_clip.py

@@ -20,23 +20,27 @@ def verify_clip(N, a_min, a_max, dtype):
     a_np, b_np = get_ref_data()
 
     def check_device(device):
-        if not tvm.module.enabled(device):
+        ctx = tvm.context(device, 0)
+        if not ctx.exist:
             print("Skip because %s is not enabled" % device)
             return
-        ctx = tvm.cpu(0) if device == "llvm" else tvm.gpu(0)
+        print("Running on target: %s" % device)
+        with tvm.target.create(device):
+            s = topi.generic.schedule_injective(B)
+
         a = tvm.nd.array(a_np, ctx)
         b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=dtype), ctx)
         f = tvm.build(s, [A, B], device, name="clip")
         f(a, b)
         np.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5)
 
-    for device in ['llvm']:
+    for device in ['llvm', 'opencl']:
         check_device(device)
 
 def test_clip():
-    verify_clip(1024, -127, 127, 'int8')
-    verify_clip(1024, -127, 127, 'int16')
     verify_clip(1024, -127, 127, 'float32')
+    verify_clip(1024, -127, 127, 'int16')
+    verify_clip(1024, -127, 127, 'int8')
 
 
 if __name__ == "__main__":

topi/tests/python/test_topi_conv2d_nchw.py

@@ -8,6 +8,8 @@ from tvm.contrib.pickle_memoize import memoize
 from topi.util import get_const_tuple
 
 def verify_conv2d_nchw(batch, in_channel, in_size, num_filter, kernel, stride, padding, dilation=1):
+    print("Workload: (%d, %d, %d, %d, %d, %d, %d)" % (batch, in_channel, in_size, num_filter, kernel, stride, padding))
+
     in_height = in_width = in_size
 
     A = tvm.placeholder((batch, in_channel, in_height, in_width), name='A')
@@ -59,7 +61,7 @@ def verify_conv2d_nchw(batch, in_channel, in_size, num_filter, kernel, stride, p
 
 
 def test_conv2d_nchw():
-    # ResNet18 worklaods
+    # ResNet18 workloads
     verify_conv2d_nchw(1, 3, 224, 64, 7, 2, 3)
     verify_conv2d_nchw(1, 64, 56, 64, 3, 1, 1)
     verify_conv2d_nchw(1, 64, 56, 64, 1, 1, 0)
@@ -72,6 +74,21 @@ def test_conv2d_nchw():
     verify_conv2d_nchw(1, 256, 14, 512, 3, 2, 1)
     verify_conv2d_nchw(1, 256, 14, 512, 1, 2, 0)
     verify_conv2d_nchw(1, 512, 7, 512, 3, 1, 1)
+    # ResNet 50 workloads
+    verify_conv2d_nchw(1, 64, 56, 256, 1, 1, 0)
+    verify_conv2d_nchw(1, 256, 56, 64, 1, 1, 0)
+    verify_conv2d_nchw(1, 256, 56, 128, 1, 2, 0)
+    verify_conv2d_nchw(1, 128, 28, 512, 1, 1, 0)
+    verify_conv2d_nchw(1, 256, 56, 512, 1, 2, 0)
+    verify_conv2d_nchw(1, 512, 28, 128, 1, 1, 0)
+    verify_conv2d_nchw(1, 512, 28, 256, 1, 2, 0)
+    verify_conv2d_nchw(1, 256, 14, 1024, 1, 1, 0)
+    verify_conv2d_nchw(1, 512, 28, 1024, 1, 2, 0)
+    verify_conv2d_nchw(1, 1024, 14, 256, 1, 1, 0)
+    verify_conv2d_nchw(1, 1024, 14, 512, 1, 2, 0)
+    verify_conv2d_nchw(1, 512, 7, 2048, 1, 2, 0)
+    verify_conv2d_nchw(1, 1024, 14, 2048, 1, 2, 0)
+    verify_conv2d_nchw(1, 2048, 7, 512, 1, 1, 0)
     # Vgg16 workloads
     verify_conv2d_nchw(1, 128, 122, 128, 3, 1, 1)
     # Super resolution workloads

topi/tests/python/test_topi_vision.py

@@ -14,7 +14,6 @@ def test_nms():
     nms_threshold = 0.7
     force_suppress = True
     nms_topk = 2
-    out = nms(data, valid_count, nms_threshold, force_suppress, nms_topk)
 
     np_data = np.array([[[0, 0.8, 1, 20, 25, 45], [1, 0.7, 30, 60, 50, 80],
                          [0, 0.4, 4, 21, 19, 40], [2, 0.9, 35, 61, 52, 79],
@@ -31,6 +30,10 @@ def test_nms():
             return
         print("Running on target: %s" % device)
         with tvm.target.create(device):
+            if device == 'llvm':
+                out = nms(data, valid_count, nms_threshold, force_suppress, nms_topk)
+            else:
+                out = topi.cuda.nms(data, valid_count, nms_threshold, force_suppress, nms_topk)
             s = topi.generic.schedule_nms(out)
 
         tvm_data = tvm.nd.array(np_data, ctx)
@@ -40,13 +43,12 @@ def test_nms():
         f(tvm_data, tvm_valid_count, tvm_out)
         np.testing.assert_allclose(tvm_out.asnumpy(), np_result, rtol=1e-4)
 
-    for device in ['llvm']:
+    for device in ['llvm', 'opencl']:
         check_device(device)
 
 
 def verify_multibox_prior(dshape, sizes=(1,), ratios=(1,), steps=(-1, -1), offsets=(0.5, 0.5), clip=False):
     data = tvm.placeholder(dshape, name="data")
-    out = ssd.multibox_prior(data, sizes, ratios, steps, offsets, clip)
 
     dtype = data.dtype
     input_data = np.random.uniform(size=dshape).astype(dtype)
@@ -88,15 +90,19 @@ def verify_multibox_prior(dshape, sizes=(1,), ratios=(1,), steps=(-1, -1), offse
             return
         print("Running on target: %s" % device)
         with tvm.target.create(device):
+            if device == 'llvm':
+                out = ssd.multibox_prior(data, sizes, ratios, steps, offsets, clip)
+            else:
+                out = topi.cuda.ssd.multibox_prior(data, sizes, ratios, steps, offsets, clip)
             s = topi.generic.schedule_multibox_prior(out)
 
         tvm_input_data = tvm.nd.array(input_data, ctx)
         tvm_out = tvm.nd.array(np.zeros(oshape, dtype=dtype), ctx)
         f = tvm.build(s, [data, out], device)
         f(tvm_input_data, tvm_out)
-        np.testing.assert_allclose(tvm_out.asnumpy(), np_out, rtol=1e-4)
+        np.testing.assert_allclose(tvm_out.asnumpy(), np_out, rtol=1e-3)
 
-    for device in ['llvm']:
+    for device in ['llvm', 'opencl']:
         check_device(device)
 
 
@@ -113,7 +119,6 @@ def test_multibox_detection():
     cls_prob = tvm.placeholder((batch_size, num_anchors, num_classes), name="cls_prob")
     loc_preds = tvm.placeholder((batch_size, num_anchors * 4), name="loc_preds")
     anchors = tvm.placeholder((1, num_anchors, 4), name="anchors")
-    out = ssd.multibox_detection(cls_prob, loc_preds, anchors)
 
     # Manually create test case
     np_cls_prob = np.array([[[0.2, 0.5, 0.3], [0.25, 0.3, 0.45], [0.7, 0.1, 0.2]]])
@@ -131,6 +136,10 @@ def test_multibox_detection():
             return
         print("Running on target: %s" % device)
         with tvm.target.create(device):
+            if device == 'llvm':
+                out = ssd.multibox_detection(cls_prob, loc_preds, anchors)
+            else:
+                out = topi.cuda.ssd.multibox_detection(cls_prob, loc_preds, anchors)
             s = topi.generic.schedule_multibox_detection(out)
 
         tvm_cls_prob = tvm.nd.array(np_cls_prob.astype(cls_prob.dtype), ctx)
@@ -141,11 +150,11 @@ def test_multibox_detection():
         f(tvm_cls_prob, tvm_loc_preds, tvm_anchors, tvm_out)
         np.testing.assert_allclose(tvm_out.asnumpy(), expected_np_out, rtol=1e-4)
 
-    for device in ['llvm']:
+    for device in ['llvm', 'opencl']:
         check_device(device)
 
 
 if __name__ == "__main__":
     test_nms()
     test_multibox_prior()
-    test_multibox_detection()
+    test_multibox_detection()
\ No newline at end of file