Add PC Incrementer - 62 tensors, 256/256 tests pass

neural_computer.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:311454049f55ce50e7fb59c9fb8f02c36a939b589cd829a28804feadc1601489
-size 668428
+oid sha256:66c5573e13ed7339e77897da494a847a31d1244dcb883cbc1d82980d20cdccf9
+size 674476

tensors.txt

@@ -1,5 +1,5 @@
 # Tensor Manifest
-# Total: 6028 tensors
+# Total: 6090 tensors
 
 alu.alu8bit.add.bias: shape=[1], values=[0.0]
 alu.alu8bit.add.weight: shape=[16], values=[1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
@@ -5615,6 +5615,68 @@ control.nop.flag_v.bias: shape=[1], values=[-0.5]
 control.nop.flag_v.weight: shape=[1], values=[1.0]
 control.nop.flag_z.bias: shape=[1], values=[-0.5]
 control.nop.flag_z.weight: shape=[1], values=[1.0]
+control.pc_inc.and1.bias: shape=[1], values=[-2.0]
+control.pc_inc.and1.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.and2.bias: shape=[1], values=[-2.0]
+control.pc_inc.and2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.and3.bias: shape=[1], values=[-2.0]
+control.pc_inc.and3.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.and4.bias: shape=[1], values=[-2.0]
+control.pc_inc.and4.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.and5.bias: shape=[1], values=[-2.0]
+control.pc_inc.and5.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.and6.bias: shape=[1], values=[-2.0]
+control.pc_inc.and6.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.and7.bias: shape=[1], values=[-2.0]
+control.pc_inc.and7.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.carry0.bias: shape=[1], values=[-0.5]
+control.pc_inc.carry0.weight: shape=[1], values=[1.0]
+control.pc_inc.overflow.bias: shape=[1], values=[-0.5]
+control.pc_inc.overflow.weight: shape=[1], values=[1.0]
+control.pc_inc.sum0.bias: shape=[1], values=[0.0]
+control.pc_inc.sum0.weight: shape=[1], values=[-1.0]
+control.pc_inc.xor1.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor1.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor1.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor1.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor1.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor1.layer2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor2.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor2.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor2.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor2.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor2.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor2.layer2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor3.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor3.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor3.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor3.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor3.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor3.layer2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor4.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor4.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor4.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor4.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor4.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor4.layer2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor5.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor5.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor5.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor5.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor5.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor5.layer2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor6.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor6.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor6.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor6.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor6.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor6.layer2.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor7.layer1.nand.bias: shape=[1], values=[1.0]
+control.pc_inc.xor7.layer1.nand.weight: shape=[2], values=[-1.0, -1.0]
+control.pc_inc.xor7.layer1.or.bias: shape=[1], values=[-1.0]
+control.pc_inc.xor7.layer1.or.weight: shape=[2], values=[1.0, 1.0]
+control.pc_inc.xor7.layer2.bias: shape=[1], values=[-2.0]
+control.pc_inc.xor7.layer2.weight: shape=[2], values=[1.0, 1.0]
 control.pop.load: shape=[1], values=[1.0]
 control.pop.sp_inc: shape=[1], values=[1.0]
 control.push.sp_dec: shape=[1], values=[1.0]

todo.md

@@ -7,7 +7,7 @@
 | SUB                     | Subtraction circuit         | DONE - 162 tensors, 65536/65536 tests pass |
 | DIV                     | Division circuit            | DONE - 1984 tensors, 65280/65280 tests pass |
 | NEG                     | Two's complement negate     | DONE - 76 tensors, 256/256 tests pass |
-| Program Counter         | PC register + increment     | Missing                        |
+| Program Counter         | PC incrementer              | DONE - 62 tensors, 256/256 tests pass |
 | PC Load                 | Load PC from jump target    | Missing                        |
 | Register File MUX       | Select 1-of-4 GPRs          | DONE - 84 tensors, 1036/1036 tests pass |
 | Register Write Enable   | Write back to register      | Missing                        |