update MLopt

openfasoc/MLoptimization/requirements.txt

@@ -7,6 +7,7 @@ klayout
 safetensors
 requests
 tensorboard
+numpy<2
 ray==2.7.1
 gym==0.26.2
 gymnasium==0.28.1

openfasoc/MLoptimization/test.py

@@ -1,31 +1,103 @@
 import numpy as np
 import glayout_import
+import sys 
 
 from sky130_nist_tapeout import safe_single_build_and_simulation
-from sky130_nist_tapeout import opamp_parameters_serializer
+from sky130_nist_tapeout import opamp_parameters_serializer, opamp_parameters_de_serializer
 
 import yaml
 from pathlib import Path
 import numpy as np
+from typing import Union
 
 params = {
-                  "diffpair_params0" : [1, 8, 1],       
-                  "diffpair_params1" : [0.5, 2.1, 0.1],   
-                  "diffpair_params2" : [1, 13, 1],
-                  "Diffpair_bias0" : [1, 8, 1],
-                  "Diffpair_bias1" : [1, 4.5, 0.5],
-                  "Diffpair_bias2" : [3, 13, 1],
-                  "pamp_hparams0" : [1, 9, 1], 
-                  "pamp_hparams1" : [0.5, 2.1, 0.1], 
-                  "pamp_hparams2" : [2, 14, 1],
-                  "bias0" : [1, 8, 1], 
-                  "bias1" : [0.5, 2.1, 0.1], 
-                  "bias2" : [3, 18, 1],
-                  "bias3" : [2, 4, 1],
-                  "half_pload1": [3, 10, 1],
-                  "half_pload3": [4, 9, 1],
-                  "mim_cap_rows" : [1, 4, 1],
-                  }
+            "diffpair_params0" : [1, 8, 1],       
+            "diffpair_params1" : [0.5, 2.1, 0.1],   
+            "diffpair_params2" : [1, 13, 1],
+            "Diffpair_bias0" : [1, 8, 1],
+            "Diffpair_bias1" : [1, 4.5, 0.5],
+            "Diffpair_bias2" : [3, 13, 1],
+            "pamp_hparams0" : [1, 9, 1], 
+            "pamp_hparams1" : [0.5, 2.1, 0.1], 
+            "pamp_hparams2" : [2, 14, 1],
+            "bias0" : [1, 8, 1], 
+            "bias1" : [0.5, 2.1, 0.1], 
+            "bias2" : [3, 18, 1],
+            "bias3" : [2, 4, 1],
+            "half_pload1": [3, 10, 1],
+            "half_pload3": [4, 9, 1],
+            "mim_cap_rows" : [1, 4, 1],
+        }
+
+def get_indices_from_ranges(opamp_parameters: Union[dict, np.array]) -> np.array:
+	"""The RL framework works by doing design searches within a user defined range for each parameter
+	For example, the RL framework may be told to search diffpair widths between 1um and 8um in steps of 1um
+	In this case, the RL framework will only ever try to make opamps with diff pair width one of [1,2,3,4,5,6,7,8]
+	this is done to limit the search space
+	The RL result will then show an index of the result. For example, if the best opamp in a design iteration had a with of 3um,
+	the corresponding index for 3um is 2 (3um is at the 2nd index in the array [1,2,3,4,5,6,7,8])
+
+	The purpose of this function to convert a list of opamp parameter into a list of indices into these range arrays
+	returns a list of indicies
+
+	input can either be given in dictionary or np.array format
+	here is an example dictionary input:
+	{'half_diffpair_params': (-987.654321, -987.654321, -987.654321), 'diffpair_bias': (-987.654321, -987.654321, -987.654321), 'half_common_source_params': (-987.654321, -987.654321, -987.654321, -987.654321), 'half_common_source_bias': (-987.654321, -987.654321, -987.654321, -987.654321), 'output_stage_params': (-987.654321, -987.654321, -987), 'output_stage_bias': (-987, -987.654321, -987.654321), 'half_pload': (-987.654321, -987.654321, -987.654321), 'mim_cap_size': (-987.654321, -987.654321), 'mim_cap_rows': -987, 'rmult': -987}
+
+	here is an example np.array indices output:
+	np.array([6, 2, 7, 6, 0, 5, 7, 0, 10, 6, 5, 13, 0, 6, 4, 2])
+	"""
+	# convert to dictionary format first
+	if isinstance(opamp_parameters, dict):
+		opamp_parameter_dict = opamp_parameters
+	else:
+		opamp_parameter_dict = opamp_parameters_de_serializer(opamp_parameters)
+	# Function to find the closest index in the range
+	def closest_index(range_params, number):
+		start, end, step = range_params
+		values = np.arange(start, end, step)
+		idx = (np.abs(values - number)).argmin()
+		return idx
+	# loop through params and find closest indices
+	opamp_parameter_arr = list()
+	for key, val in params.items():
+		if key == "diffpair_params0":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_diffpair_params"][0]))
+		elif key == "diffpair_params1":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_diffpair_params"][1]))
+		elif key == "diffpair_params2":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_diffpair_params"][2]))
+		elif key == "Diffpair_bias0":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["diffpair_bias"][0]))
+		elif key == "Diffpair_bias1":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["diffpair_bias"][1]))
+		elif key == "Diffpair_bias2":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["diffpair_bias"][2]))
+		elif key == "pamp_hparams0":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_params"][0]))
+		elif key == "pamp_hparams1":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_params"][1]))
+		elif key == "pamp_hparams2":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_params"][2]))
+		elif key == "bias0":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_bias"][0]))
+		elif key == "bias1":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_bias"][1]))
+		elif key == "bias2":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_bias"][2]))
+		elif key == "bias3":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_common_source_bias"][3]))
+		elif key == "half_pload1":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_pload"][0]))
+		elif key == "half_pload3":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["half_pload"][2]))
+		elif key == "mim_cap_rows":
+			opamp_parameter_arr.append(closest_index(val, opamp_parameter_dict["mim_cap_rows"]))
+		else:
+			raise ValueError("invalid key")
+	# this relies on the fact that the params dict should be in order
+	return np.array(opamp_parameter_arr)
+
 paramss = []
 params_id = list(params.keys())
 
@@ -46,7 +118,6 @@
 inputparam[22] = paramsss[14]
 inputparam[25] = paramsss[15]
 
-
 result = safe_single_build_and_simulation(inputparam, hardfail=True)
 
 print(result)

openfasoc/generators/glayout/tapeout/tapeout_and_RL/sky130_nist_tapeout.py

@@ -1,16 +1,20 @@
 import sys
 from os import path, rename, environ
 environ['OPENBLAS_NUM_THREADS'] = '1'
+from pathlib import Path
 # path to glayout
-sys.path.append(path.join(path.dirname(__file__), '../../'))
-
+sys.path.append(path.join(str(Path(__file__).resolve().parents[2])))
 from gdsfactory.read.import_gds import import_gds
 from gdsfactory.components import text_freetype, rectangle
 from glayout.flow.pdk.util.comp_utils import prec_array, movey, align_comp_to_port, prec_ref_center
 from glayout.flow.pdk.util.port_utils import add_ports_perimeter, print_ports
 from gdsfactory.component import Component
 from glayout.flow.pdk.mappedpdk import MappedPDK
-from glayout.flow.blocks.composite.opamp import opamp
+try:
+	from glayout.flow.blocks.composite.opamp import opamp
+except: 
+    print('Regular opamp import failed! Using Fallback...')
+    from glayout.flow.blocks.opamp import opamp
 from glayout.flow.routing.L_route import L_route
 from glayout.flow.routing.straight_route import straight_route
 from glayout.flow.routing.c_route import c_route