From afa32b950b812bd0a40c3f8b14a848e80c18f881 Mon Sep 17 00:00:00 2001
From: Yaman Umuroglu <yamanu@xilinx.com>
Date: Wed, 21 Aug 2019 13:39:03 +0000
Subject: [PATCH] sketch some basics for datatypes and the Tensor type
---
src/finn/core/tensor.py | 121 ++++++++++++++++++++++++++++++++++++++++
1 file changed, 121 insertions(+)
create mode 100644 src/finn/core/tensor.py
diff --git a/src/finn/core/tensor.py b/src/finn/core/tensor.py
new file mode 100644
index 000000000..274f66d7f
--- /dev/null
+++ b/src/finn/core/tensor.py
@@ -0,0 +1,121 @@
+# Copyright (c) 2018, Xilinx
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+#
+# 1. Redistributions of source code must retain the above copyright
+# notice, this list of conditions and the following disclaimer.
+# 2. Redistributions in binary form must reproduce the above copyright
+# notice, this list of conditions and the following disclaimer in the
+# documentation and/or other materials provided with the distribution.
+# 3. Neither the name of the <organization> nor the
+# names of its contributors may be used to endorse or promote products
+# derived from this software without specific prior written permission.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
+# ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
+# WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+# DISCLAIMED. IN NO EVENT SHALL <COPYRIGHT HOLDER> BE LIABLE FOR ANY
+# DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
+# (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
+# LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
+# ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+# SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+import numpy as np
+from enum import Enum
+
+class DataType(Enum):
+ FLOAT32 = 0
+ BINARY = 1
+ BIPOLAR = 2
+ UINT2 = 3
+ UINT3 = 4
+ UINT4 = 5
+ UINT8 = 6
+ UINT16 = 7
+ UINT32 = 8
+ INT2 = 9
+ INT3 = 10
+ INT4 = 11
+ INT8 = 12
+ INT16 = 13
+ INT32 = 14
+
+ def bitwidth(self):
+ """Returns the number of bits required for this DataType."""
+
+ if self.name.startswith("UINT"):
+ return int(self.name.strip("UINT"))
+ elif self.name.startswith("INT"):
+ return int(self.name.strip("INT"))
+ elif "FLOAT" in self.name:
+ return int(self.name.strip("FLOAT"))
+ elif self.name in ["BINARY", "BIPOLAR"]:
+ return 1
+ else:
+ raise Exception("Unrecognized data type: %s" % self.name)
+
+ def min(self):
+ """Returns the smallest possible value allowed by this DataType."""
+
+ if self.name.startswith("UINT") or self.name == "BINARY":
+ return 0
+ elif self.name.startswith("INT"):
+ return -(2 ** (self.bitwidth() - 1))
+ elif self.name == "FLOAT32":
+ return np.finfo(np.float32).min
+ elif self.name == "BIPOLAR":
+ return -1
+ else:
+ raise Exception("Unrecognized data type: %s" % self.name)
+
+ def max(self):
+ """Returns the largest possible value allowed by this DataType."""
+
+ if self.name.startswith("UINT"):
+ return (2 ** (self.bitwidth())) - 1
+ elif self.name == "BINARY":
+ return +1
+ elif self.name.startswith("INT"):
+ return (2 ** (self.bitwidth() - 1)) - 1
+ elif self.name == "FLOAT32":
+ return np.finfo(np.float32).max
+ elif self.name == "BIPOLAR":
+ return +1
+ else:
+ raise Exception("Unrecognized data type: %s" % self.name)
+
+ def allowed(self, value):
+ """Check whether given value is allowed for this DataType.
+
+ value (float32): value to be checked"""
+
+ if "FLOAT" in self.name:
+ return True
+ elif "INT" in self.name:
+ return (self.min() <= value) and (value <= self.max())
+ elif self.name == "BINARY":
+ return value in [0, 1]
+ elif self.name == "BIPOLAR":
+ return value in [-1, +1]
+ else:
+ raise Exception("Unrecognized data type: %s" % self.name)
+
+class Tensor(object):
+ """A multidimensional array of numbers of given datatype.
+
+ Attributes:
+ dtype (DataType): Element data type for this Tensor
+ data (numpy ndarray of float32): Numpy container for data
+ ndims (int): Number of dimensions in array, 0 indicates scalar
+ dim_names (list of str): names associated with each dimension, e.g.
+ ["N", "C", "H", "W"]
+ """
+
+ def __init__(self, dtype, data, dim_names = []):
+ self.dtype = dtype
+ self.data = data
+ self.dim_names = dim_names
--
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