def _checkRenderParameters(parms):
"""Check the values of the render-specific parameters.
Return True if the values are valid and False otherwise.
"""
if parms["max_hosts_per_job"] < parms["min_hosts_per_job"]:
hqrop.displayError(
"Max. Hosts Per Job must be greater than or equal to "
"Min. Hosts Per Job.")
return False
# Check IFD file path.
if parms["make_ifds"] or not parms["use_output_driver"]:
if not parms["ifd_path"]:
if parms["make_ifds"]:
ifd_path_parm = hou.parm("hq_outputifd")
elif not parms["use_output_driver"]:
ifd_path_parm = hou.parm("hq_input_ifd")
ifd_parm_label = ifd_path_parm.parmTemplate().label()
hqrop.displayError(" ".join(["The value of the", ifd_parm_label,
"parameter in\n", hou.pwd().path(), "\n"
"must not be blank."]))
return False
return True
def _checkRenderParameters(parms):
"""Check the values of the render-specific parameters.
Return True if the values are valid and False otherwise.
"""
if parms["max_hosts_per_job"] < parms["min_hosts_per_job"]:
hqrop.displayError(
"Max. Hosts Per Job must be greater than or equal to "
"Min. Hosts Per Job.")
return False
# Check IFD file path.
if parms["make_ifds"] or not parms["use_output_driver"]:
if not parms["ifd_path"]:
if parms["make_ifds"]:
ifd_path_parm = hou.parm("hq_outputifd")
elif not parms["use_output_driver"]:
ifd_path_parm = hou.parm("hq_input_ifd")
ifd_parm_label = ifd_path_parm.parmTemplate().label()
hqrop.displayError(" ".join([
"The value of the", ifd_parm_label, "parameter in\n",
hou.pwd().path(), "\n"
"must not be blank."
]))
return False
return True
def render():
"""Evaluate and package the HDA parameters and submit a job to HQueue."""
# Build a dictionary of base parameters and add the HQueue Render-specific
# ones.
parms = hqrop.getBaseParameters()
use_cloud = (hou.ch("hq_use_cloud1")
if hou.parm("hq_use_cloud1") is not None else 0)
num_cloud_machines = (hou.ch("hq_num_cloud_machines")
if hou.parm("hq_num_cloud_machines") is not None else 0)
machine_type = (hou.ch("hq_cloud_machine_type")
if hou.parm("hq_cloud_machine_type") is not None else "")
use_output_driver = bool(use_cloud) or parms["hip_action"] != "use_ifd"
# validate the machine type
if machine_type not in ['c1.medium', 'c1.xlarge',
'm1.small', 'm1.large', 'm1.xlarge']:
machine_type = 'c1.xlarge'
parms.update({
"assign_ifdgen_to" : hou.parm("hq_assign_ifdgen_to").evalAsString(),
"ifdgen_clients": hou.ch("hq_ifdgen_clients").strip(),
"ifdgen_client_groups" : hou.ch("hq_ifdgen_client_groups").strip(),
"batch_all_frames": hou.ch("hq_batch_all_frames"),
"frames_per_job": hou.ch("hq_framesperjob"),
"render_frame_order": hou.parm("hq_render_frame_order").evalAsString(),
"make_ifds": hou.ch("hq_makeifds"),
"max_hosts_per_job": hou.ch("hq_max_hosts"),
"min_hosts_per_job": hou.ch("hq_min_hosts"),
"is_CPU_number_set": bool(hou.ch("hq_is_CPU_number_set")),
"CPUs_to_use": hou.ch("hq_CPUs_to_use"),
"output_ifd": hou.parm("hq_outputifd").unexpandedString().strip(),
"use_output_driver" : use_output_driver,
"use_cloud": use_cloud,
"num_cloud_machines": num_cloud_machines,
"cloud_machine_type" : machine_type,
"use_render_tracker" : hou.ch("hq_use_render_tracker"),
"delete_ifds": hou.ch("hq_delete_ifds"),
"render_single_tile": bool(hou.ch("hq_render_single_tile")),
})
if use_output_driver:
# Convert output_driver path to an absolute path.
parms["output_driver"] = hou.ch("hq_driver").strip()
rop_node = hou.pwd().node(parms["output_driver"])
if rop_node:
parms["output_driver"] = rop_node.path()
parms["ifd_path"] = hou.parm("hq_outputifd").unexpandedString().strip()
output_driver = hqrop.getOutputDriver(hou.pwd())
# Turn "off" Mantra-specific parameters if there is an output driver
# and it is not a Mantra ROP.
if output_driver and output_driver.type().name() != "ifd":
parms["make_ifds"] = False
parms["min_hosts_per_job"] = 1
parms["max_hosts_per_job"] = 1
else:
parms.update({
"ifd_path" : hou.parm("hq_input_ifd").unexpandedString().strip(),
"start_frame" : hou.ch("hq_frame_range_1"),
"end_frame" : hou.ch("hq_frame_range_2"),
"frame_skip" : hou.ch("hq_frame_range_3"),
# If we are not using an output driver we are using IFDs and so
# we won't be making them
"make_ifds" : False,
})
if parms["frame_skip"] <= 0:
parms["frame_skip"] = 1
# We stop if we cannot establish a connection with the server
if (not parms["use_cloud"]
and not hqrop.doesHQServerExists(parms["hq_server"])):
return None
if "ifd_path" in parms and not parms["use_cloud"]:
expand_frame_variables = False
parms["ifd_path"] = hqrop.substituteWithHQROOT(
parms["hq_server"], parms["ifd_path"], expand_frame_variables)
# Validate parameter values.
if (not hqrop.checkBaseParameters(parms) or
not _checkRenderParameters(parms)):
return
if use_output_driver and parms["hip_action"] == "use_current_hip":
if not hqrop.checkOutputDriver(parms["output_driver"]):
return
if hqrop.checkForRecursiveChain(hou.pwd()):
hqrop.displayError(("Cannot submit HQueue job because"
" %s is in the input chain of %s.")
% (hou.pwd().path(), parms["output_driver"]))
return
# If we're not supposed to run this job on the cloud, submit the job.
# Otherwise, we'll display the file dependency dialog.
if parms["use_cloud"]:
# We don't want to keep the interrupt dialog open, so we exit this soho
# script so the dialog closes and schedule an event to run the code to
# display the dialog.
import soho
rop_node = hou.node(soho.getOutputDriver().getName())
cloud.selectProjectParmsForCloudRender(
rop_node, parms["num_cloud_machines"], parms["cloud_machine_type"])
return
# Automatically save changes to the .hip file,
# or at least warn the user about unsaved changes.
should_continue = hqrop.warnOrAutoSaveHipFile(parms)
if not should_continue:
return
hqrop.submitJob(parms, _byu_troubleshoot_hq)
def render():
"""Evaluate and package the HDA parameters and submit a job to HQueue."""
# Build a dictionary of base parameters and add the HQueue Render-specific
# ones.
parms = hqrop.getBaseParameters()
use_cloud = (hou.ch("hq_use_cloud1")
if hou.parm("hq_use_cloud1") is not None else 0)
num_cloud_machines = (hou.ch("hq_num_cloud_machines") if
hou.parm("hq_num_cloud_machines") is not None else 0)
machine_type = (hou.ch("hq_cloud_machine_type")
if hou.parm("hq_cloud_machine_type") is not None else "")
use_output_driver = bool(use_cloud) or parms["hip_action"] != "use_ifd"
# validate the machine type
if machine_type not in [
'c1.medium', 'c1.xlarge', 'm1.small', 'm1.large', 'm1.xlarge'
]:
machine_type = 'c1.xlarge'
parms.update({
"assign_ifdgen_to":
hou.parm("hq_assign_ifdgen_to").evalAsString(),
"ifdgen_clients":
hou.ch("hq_ifdgen_clients").strip(),
"ifdgen_client_groups":
hou.ch("hq_ifdgen_client_groups").strip(),
"batch_all_frames":
hou.ch("hq_batch_all_frames"),
"frames_per_job":
hou.ch("hq_framesperjob"),
"render_frame_order":
hou.parm("hq_render_frame_order").evalAsString(),
"make_ifds":
hou.ch("hq_makeifds"),
"max_hosts_per_job":
hou.ch("hq_max_hosts"),
"min_hosts_per_job":
hou.ch("hq_min_hosts"),
"is_CPU_number_set":
bool(hou.ch("hq_is_CPU_number_set")),
"CPUs_to_use":
hou.ch("hq_CPUs_to_use"),
"output_ifd":
hou.parm("hq_outputifd").unexpandedString().strip(),
"use_output_driver":
use_output_driver,
"use_cloud":
use_cloud,
"num_cloud_machines":
num_cloud_machines,
"cloud_machine_type":
machine_type,
"use_render_tracker":
hou.ch("hq_use_render_tracker"),
"delete_ifds":
hou.ch("hq_delete_ifds"),
"render_single_tile":
bool(hou.ch("hq_render_single_tile")),
})
if use_output_driver:
# Convert output_driver path to an absolute path.
parms["output_driver"] = hou.ch("hq_driver").strip()
rop_node = hou.pwd().node(parms["output_driver"])
if rop_node:
parms["output_driver"] = rop_node.path()
parms["ifd_path"] = hou.parm("hq_outputifd").unexpandedString().strip()
output_driver = hqrop.getOutputDriver(hou.pwd())
# Turn "off" Mantra-specific parameters if there is an output driver
# and it is not a Mantra ROP.
if output_driver and output_driver.type().name() != "ifd":
parms["make_ifds"] = False
parms["min_hosts_per_job"] = 1
parms["max_hosts_per_job"] = 1
else:
parms.update({
"ifd_path":
hou.parm("hq_input_ifd").unexpandedString().strip(),
"start_frame":
hou.ch("hq_frame_range_1"),
"end_frame":
hou.ch("hq_frame_range_2"),
"frame_skip":
hou.ch("hq_frame_range_3"),
# If we are not using an output driver we are using IFDs and so
# we won't be making them
"make_ifds":
False,
})
if parms["frame_skip"] <= 0:
parms["frame_skip"] = 1
# We stop if we cannot establish a connection with the server
if (not parms["use_cloud"]
and not hqrop.doesHQServerExists(parms["hq_server"])):
return None
if "ifd_path" in parms and not parms["use_cloud"]:
expand_frame_variables = False
parms["ifd_path"] = hqrop.substituteWithHQROOT(parms["hq_server"],
parms["ifd_path"],
expand_frame_variables)
# Validate parameter values.
if (not hqrop.checkBaseParameters(parms)
or not _checkRenderParameters(parms)):
return
if use_output_driver and parms["hip_action"] == "use_current_hip":
if not hqrop.checkOutputDriver(parms["output_driver"]):
return
if hqrop.checkForRecursiveChain(hou.pwd()):
hqrop.displayError(("Cannot submit HQueue job because"
" %s is in the input chain of %s.") %
(hou.pwd().path(), parms["output_driver"]))
return
# If we're not supposed to run this job on the cloud, submit the job.
# Otherwise, we'll display the file dependency dialog.
if parms["use_cloud"]:
# We don't want to keep the interrupt dialog open, so we exit this soho
# script so the dialog closes and schedule an event to run the code to
# display the dialog.
import soho
rop_node = hou.node(soho.getOutputDriver().getName())
cloud.selectProjectParmsForCloudRender(rop_node,
parms["num_cloud_machines"],
parms["cloud_machine_type"])
return
# Automatically save changes to the .hip file,
# or at least warn the user about unsaved changes.
should_continue = hqrop.warnOrAutoSaveHipFile(parms)
if not should_continue:
return
hqrop.submitJob(parms, _byu_troubleshoot_hq)
