def render(self, is_lock):
bimpy.indent(10)
bimpy.text('- Plane')
bimpy.same_line()
bimpy_tools.help_marker(
'generate with random points\n' \
'* plane random: random on whole plane\n' \
'* balanced random: balanced positive and negative samples'
)
bimpy.push_item_width(140)
if bimpy.begin_combo('strategy##plane_random_generator',
self._select_strategy):
for item in self._strategy_list:
is_selected = bimpy.Bool(self._select_strategy == item)
if bimpy.selectable(item, is_selected) and not is_lock:
self._select_strategy = item
if is_selected.value:
bimpy.set_item_default_focus()
bimpy.end_combo()
bimpy.pop_item_width()
bimpy.unindent(10)
def render(self, is_lock):
bimpy.indent(10)
bimpy.text('- Linear layer init')
bimpy.same_line()
bimpy_tools.help_marker(
'Initializer used in torch.nn.Linear, use Kaiming uniform')
bimpy.push_item_width(120)
flags = bimpy.InputTextFlags.EnterReturnsTrue
if is_lock:
flags |= bimpy.InputTextFlags.ReadOnly
if bimpy.input_float('a##sgd_optimizer', self._a, flags=flags):
self._a.value = max(0.0, self._a.value)
if bimpy.begin_combo('mode##linear_layer_init', self._select_mode):
for item in self._mode_list:
is_selected = bimpy.Bool(self._select_mode == item)
if bimpy.selectable(item, is_selected) and not is_lock:
self._select_mode = item
if is_selected.value:
bimpy.set_item_default_focus()
bimpy.end_combo()
if bimpy.begin_combo('nonlinearity##linear_layer_init',
self._select_nonlinearity):
for item in self._nonlinearity_list:
is_selected = bimpy.Bool(self._select_nonlinearity == item)
if bimpy.selectable(item, is_selected) and not is_lock:
self._select_nonlinearity = item
if is_selected.value:
bimpy.set_item_default_focus()
bimpy.end_combo()
bimpy.pop_item_width()
bimpy.unindent(10)
def render(self, is_lock):
bimpy.set_next_tree_node_open(True, bimpy.Condition.FirstUseEver)
if not bimpy.tree_node('optimizer##optimizer_component'):
return
if bimpy.begin_combo('select##optimizer_component',
self._select_optimizer):
for item in self._optimizer_list:
is_selected = bimpy.Bool(self._select_optimizer == item)
if bimpy.selectable(item, is_selected) and not is_lock:
self._select_optimizer = item
if is_selected.value:
bimpy.set_item_default_focus()
bimpy.end_combo()
self._optimizer_map[self._select_optimizer].render(is_lock)
bimpy.tree_pop()
def render(self, is_lock):
bimpy.indent(10)
bimpy.text('- MSE loss')
bimpy.same_line()
bimpy_tools.help_marker('torch.nn.MSELoss')
bimpy.push_item_width(120)
if bimpy.begin_combo('reduction##mse_loss_fn', self._select_redution):
for item in self._reduction_list:
is_selected = bimpy.Bool(self._select_redution == item)
if bimpy.selectable(item, is_selected) and not is_lock:
self._select_redution = item
if is_selected.value:
bimpy.set_item_default_focus()
bimpy.end_combo()
bimpy.pop_item_width()
bimpy.unindent(10)
def render(self, is_lock):
bimpy.indent(10)
bimpy.text('- Raw Point')
bimpy.same_line()
bimpy_tools.help_marker('generate with raw points')
bimpy.push_item_width(120)
if bimpy.begin_combo('strategy##raw_point_generator',
self._select_strategy):
for item in self._strategy_list:
is_selected = bimpy.Bool(self._select_strategy == item)
if bimpy.selectable(item, is_selected) and not is_lock:
self._select_strategy = item
if is_selected.value:
bimpy.set_item_default_focus()
bimpy.end_combo()
bimpy.pop_item_width()
bimpy.unindent(10)
