[PYNQ] pad innermost dimension only

src/finn/transformation/fpgadataflow/make_pynq_proj.py

 import os
 import subprocess
 
-import numpy as np
-
 from finn.transformation import Transformation
 from finn.util.basic import get_by_name, make_build_dir, roundup_to_integer_multiple
 
@@ -53,21 +51,22 @@ class MakePYNQProject(Transformation):
         ip_dirs_str = "[%s]" % (" ".join(ip_dirs))
 
         # extract the actual in-out bytes from graph
+        # TODO convert this to an analysis pass
         i_tensor_name = model.graph.input[0].name
         o_tensor_name = model.graph.output[0].name
         i_tensor_shape = model.get_tensor_shape(i_tensor_name)
         o_tensor_shape = model.get_tensor_shape(o_tensor_name)
         i_tensor_dt = model.get_tensor_datatype(i_tensor_name)
         o_tensor_dt = model.get_tensor_datatype(o_tensor_name)
-        i_bits = i_tensor_dt.bitwidth() * np.prod(i_tensor_shape)
-        o_bits = o_tensor_dt.bitwidth() * np.prod(o_tensor_shape)
+        i_bits_per_cycle = i_tensor_dt.bitwidth() * i_tensor_shape[-1]
+        o_bits_per_cycle = o_tensor_dt.bitwidth() * o_tensor_shape[-1]
         # ensure i/o is padded to bytes
-        i_bits = roundup_to_integer_multiple(i_bits, 8)
-        o_bits = roundup_to_integer_multiple(o_bits, 8)
-        assert i_bits % 8 == 0
-        assert o_bits % 8 == 0
-        in_bytes = i_bits / 8
-        out_bytes = o_bits / 8
+        i_bits_per_cycle_padded = roundup_to_integer_multiple(i_bits_per_cycle, 8)
+        o_bits_per_cycle_padded = roundup_to_integer_multiple(o_bits_per_cycle, 8)
+        assert i_bits_per_cycle_padded % 8 == 0
+        assert i_bits_per_cycle_padded % 8 == 0
+        in_bytes = i_bits_per_cycle_padded / 8
+        out_bytes = o_bits_per_cycle_padded / 8
         in_if_name = "in0_V_V_0"
         out_if_name = "out_r_0"
         clk_name = "ap_clk_0"