[VTA][Relay] Relay Compilation + AutoTVM compatible operator librarie…

…s for VTA (apache#3135)

include/vta/driver.h

@@ -42,7 +42,7 @@ extern "C" {
 
 /*! \brief Physically contiguous buffer size limit */
 #ifndef VTA_MAX_XFER
-#define VTA_MAX_XFER (1<<22)
+#define VTA_MAX_XFER (1<<25)
 #endif
 
 /*! PAGE SIZE */

python/vta/build_module.py

@@ -14,6 +14,7 @@
 # KIND, either express or implied.  See the License for the
 # specific language governing permissions and limitations
 # under the License.
+# pylint: disable=unused-argument
 """VTA specific buildin for runtime."""
 from __future__ import absolute_import as _abs
 

python/vta/environment.py

@@ -234,6 +234,10 @@ def gemm(self):
         """GEMM intrinsic"""
         return self.dev.gemm
 
+    @property
+    def target(self):
+        return tvm.target.vta(model=self.TARGET)
+
     @property
     def target_host(self):
         """The target host"""
@@ -243,6 +247,9 @@ def target_host(self):
             return "llvm"
         raise ValueError("Unknown target %s" % self.TARGET)
 
+    @property
+    def target_vta_cpu(self):
+        return tvm.target.arm_cpu(model=self.TARGET)
 
 def get_env():
     """Get the current VTA Environment.

python/vta/exec/rpc_server.py

@@ -66,6 +66,9 @@ def ext_dev_callback():
 
     @tvm.register_func("tvm.contrib.vta.init", override=True)
     def program_fpga(file_name):
+        from pynq import xlnk
+        # Reset xilinx driver
+        xlnk.Xlnk().xlnk_reset()
         path = tvm.get_global_func("tvm.rpc.server.workpath")(file_name)
         env = get_env()
         program_bitstream.bitstream_program(env.TARGET, path)

python/vta/pkg_config.py

@@ -77,8 +77,6 @@ def __init__(self, cfg, proj_root):
         if self.target == "pynq":
             self.ldflags = [
                 "-L/usr/lib",
-                "-L/opt/python3.6/lib/python3.6/site-packages/pynq/drivers/",
-                "-L/opt/python3.6/lib/python3.6/site-packages/pynq/lib/",
                 "-l:libcma.so"]
         else:
             self.ldflags = []

python/vta/testing/simulator.py

@@ -84,4 +84,17 @@ def tsim_cycles():
     """
     return tvm.get_global_func("tvm.vta.tsim.cycles")()
 
+# debug flag to skip execution.
+DEBUG_SKIP_EXEC = 1
+
+def debug_mode(flag):
+    """Set debug mode
+    Paramaters
+    ----------
+    flag : int
+        The debug flag, 0 means clear all flags.
+    """
+    tvm.get_global_func("vta.simulator.profiler_debug_mode")(flag)
+
+
 LIBS = _load_lib()

python/vta/testing/util.py

@@ -18,7 +18,7 @@
 from __future__ import absolute_import as _abs
 
 import os
-from tvm import rpc
+from tvm import rpc, autotvm
 from ..environment import get_env
 from . import simulator
 
@@ -42,7 +42,7 @@ def run(run_func):
         # the port it's listening to, e.g. 9090
         local_rpc = int(os.environ.get("VTA_LOCAL_SIM_RPC", "0"))
         if local_rpc:
-            remote = rpc.connect("localhost", local_rpc)
+            remote = rpc.connect("127.0.0.1", local_rpc)
             run_func(env, remote)
         else:
             # Make sure simulation library exists
@@ -54,12 +54,22 @@ def run(run_func):
 
     elif env.TARGET == "pynq":
 
-        # Run on PYNQ if env variable exists
-        host = os.environ.get("VTA_PYNQ_RPC_HOST", None)
-        port = int(os.environ.get("VTA_PYNQ_RPC_PORT", None))
-        if host and port:
-            remote = rpc.connect(host, port)
+        tracket_host = os.environ.get("TVM_TRACKER_HOST", None)
+        tracket_port = int(os.environ.get("TVM_TRACKER_PORT", None))
+        pynq_host = os.environ.get("VTA_PYNQ_RPC_HOST", None)
+        pynq_port = int(os.environ.get("VTA_PYNQ_RPC_PORT", None))
+        # Run device from fleet node if env variables are defined
+        if tracket_host and tracket_port:
+            remote = autotvm.measure.request_remote(env.TARGET,
+                                                    tracket_host,
+                                                    tracket_port,
+                                                    timeout=10000)
             run_func(env, remote)
         else:
-            raise RuntimeError(
-                "Please set the VTA_PYNQ_RPC_HOST and VTA_PYNQ_RPC_PORT environment variables")
+            # Next, run on PYNQ if env variables are defined
+            if pynq_host and pynq_port:
+                remote = rpc.connect(pynq_host, pynq_port)
+                run_func(env, remote)
+            else:
+                raise RuntimeError(
+                    "Please set the VTA_PYNQ_RPC_HOST and VTA_PYNQ_RPC_PORT environment variables")

python/vta/top/__init__.py

@@ -1,5 +1,12 @@
 """TVM TOPI connector, eventually most of these should go to TVM repo"""
 
-from .vta_conv2d import packed_conv2d, schedule_packed_conv2d
+from . import bitpack
+from .graphpack import graph_pack
+from . import op
 from . import vta_conv2d
-from . import arm_conv2d
+from . import vta_dense
+
+# NNVM is deprecated for VTA
+# from . import nnvm_bitpack
+# from .nnvm_graphpack import nnvm_graph_pack
+# from . import nnvm_op

python/vta/top/bitpack.py

@@ -0,0 +1,90 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+# pylint: disable=ungrouped-imports
+
+"""Bit packing operators"""
+from __future__ import absolute_import as _abs
+
+import tvm
+from topi import util
+
+from tvm.relay.op.op import register_compute, register_schedule
+from tvm.relay.op.op import register_pattern, OpPattern
+from tvm.relay.op.op import schedule_injective
+
+def bitpack(data, bits, pack_type="int8", name="bitpack"):
+    """Packs lowest dimension into format needed by VTA
+
+    Parameters
+    ----------
+    pack_axis : int
+        index of the axis to pack in data
+    bit_axis : int
+        index of axis to place bit axis in resulting packed data
+
+    Returns
+    -------
+    packed : Tensor
+        The packed tensor.
+    """
+    shape_vec = list(data.shape)
+    if pack_type == 'int8':
+        data_width = 8
+    elif pack_type == 'int16':
+        data_width = 16
+    elif pack_type == 'int32':
+        data_width = 32
+    else:
+        raise RuntimeError("Unknown pack type %s" % pack_type)
+    assert data_width % bits == 0
+    lanes = data_width // bits
+
+    # Data must be in multiples of the data_width
+    assert util.get_const_int(shape_vec[-1]) % lanes == 0, "Not a multiple of word size"
+    shape_vec[-1] = shape_vec[-1] // lanes
+    oshape = tuple(shape_vec)
+
+    def _bitpack(*indices):
+        ret = None
+        mask = tvm.const((1 << bits) - 1, pack_type)
+        for k in range(lanes):
+            idx = list(indices)
+            idx[-1] = idx[-1] * lanes + k
+            elem = data(*idx).astype(pack_type)
+            if k == 0:
+                ret = elem & mask
+            else:
+                val = (elem & mask) << tvm.const(k * bits, pack_type)
+                ret = ret | val
+        return ret
+
+    return tvm.compute(
+        oshape, _bitpack, name=name, tag='bitpack')
+
+
+@register_compute("bitpack", level=15)
+def compute_bitpack(attrs, inputs):
+    lanes = attrs.lanes
+    dtype = inputs[0].dtype
+    assert dtype == "int8"
+    width = 8
+    assert width % lanes == 0
+    bits = 8 // lanes
+    return bitpack(inputs[0], bits, dtype)
+
+register_schedule("bitpack", schedule_injective)
+register_pattern("bitpack", OpPattern.INJECTIVE)