From d155aec10a801352f8e83367c6d43511188dee34 Mon Sep 17 00:00:00 2001
From: Jared Roesch <roeschinc@gmail.com>
Date: Fri, 7 Dec 2018 00:26:00 -0800
Subject: [PATCH] Add relay_bitpack.py (#36)

---
 vta/python/vta/top/relay_bitpack.py | 72 +++++++++++++++++++++++++++++
 1 file changed, 72 insertions(+)
 create mode 100644 vta/python/vta/top/relay_bitpack.py

diff --git a/vta/python/vta/top/relay_bitpack.py b/vta/python/vta/top/relay_bitpack.py
new file mode 100644
index 000000000000..2265af4518b4
--- /dev/null
+++ b/vta/python/vta/top/relay_bitpack.py
@@ -0,0 +1,72 @@
+"""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, output_type, target):
+    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)