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<title>Dask Performance Report</title>
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**kwargs)\n","ret = self._cache[fun] = fun(self)\n","with open_binary(\"%s/%s/stat\" % (self._procfs_path, self.pid)) as f:\n","return open(fname, \"rb\", **kwargs)\n","ret = self._cache[fun] = fun(self)\n","return self._proc.memory_info()\n","return fun(self, *args, **kwargs)\n","with open_binary(\"%s/%s/statm\" % (self._procfs_path, self.pid)) as f:\n","return open(fname, \"rb\", **kwargs)\n","state = profile.process(\n","state = process(prev, frame, state, stop=stop)\n","state = process(prev, frame, state, stop=stop)\n","state = process(prev, frame, state, stop=stop)\n","state = process(prev, frame, state, stop=stop)\n","\"description\": info_frame(frame),\n","line = linecache.getline(co.co_filename, frame.f_lineno, frame.f_globals).lstrip()\n","lines = getlines(filename, module_globals)\n","return updatecache(filename, module_globals)\n","return lines\n","return text\n","state = process(prev, frame, state, stop=stop)\n","\"description\": info_frame(frame),\n","line = linecache.getline(co.co_filename, frame.f_lineno, frame.f_globals).lstrip()\n","lines = getlines(filename, module_globals)\n","return updatecache(filename, module_globals)\n","with tokenize.open(fullname) as fp:\n","buffer = _builtin_open(filename, 'rb')\n","line = linecache.getline(co.co_filename, frame.f_lineno, frame.f_globals).lstrip()\n","lines = getlines(filename, module_globals)\n","return updatecache(filename, module_globals)\n","stat = os.stat(fullname)\n","line = linecache.getline(co.co_filename, frame.f_lineno, frame.f_globals).lstrip()\n","lines = getlines(filename, module_globals)\n","return updatecache(filename, module_globals)\n","with tokenize.open(fullname) as fp:\n","encoding, lines = detect_encoding(buffer.readline)\n","first = read_or_stop()\n","return readline()\n","line = linecache.getline(co.co_filename, frame.f_lineno, frame.f_globals).lstrip()\n","lines = getlines(filename, module_globals)\n","return updatecache(filename, module_globals)\n","lines = 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<h1> Dask Performance Report </h1>\n\n <i> Select different tabs on the top for additional information </i>\n\n <h2> Duration: 49.53 s </h2>\n <h2> Tasks Information </h2>\n <ul>\n <li> number of tasks: 1704 </li>\n \n<li> compute time: 264.55 s </li>\n<li> deserialize time: 229.59 ms </li>\n </ul>\n\n <h2> Scheduler Information </h2>\n <ul>\n <li> Address: inproc://192.168.68.109/25154/1 </li>\n <li> Workers: 1 </li>\n <li> Threads: 6 </li>\n <li> Memory: 0 B </li>\n <li> Dask Version: 2021.05.0 </li>\n <li> Dask.Distributed Version: 2021.05.0 </li>\n </ul>\n\n <h2> Calling Code </h2>\n <pre>\ndef _execute(exitstack):\n \"\"\"Runs the application.\"\"\"\n\n opts = parser.parse_inputs()\n\n # TODO: This check needs to be fleshed out substantially.\n\n preprocess.check_opts(opts)\n preprocess.interpret_model(opts)\n\n if opts.parallel_scheduler == \"distributed\":\n if opts.parallel_address:\n logger.info(\"Initializing distributed client.\")\n client = exitstack.enter_context(Client(opts.parallel_address))\n else:\n logger.info(\"Initializing distributed client using LocalCluster.\")\n cluster = LocalCluster(processes=opts.parallel_nworker > 1,\n n_workers=opts.parallel_nworker,\n threads_per_worker=opts.parallel_nthread,\n memory_limit=0)\n cluster = exitstack.enter_context(cluster)\n client = exitstack.enter_context(Client(cluster))\n\n # Install Quartical Scheduler Plugin\n # Controversial from a security POV,\n # run_on_scheduler is a debugging function\n # `dask-scheduler --preload install_plugin.py`\n # is the standard but less convenient pattern\n client.run_on_scheduler(install_plugin)\n\n logger.info(\"Distributed client sucessfully initialized.\")\n\n t0 = time.time()\n\n # Reads the measurement set using the relavant configuration from opts.\n data_xds_list, ref_xds_list = read_xds_list(opts)\n data_xds_list = data_xds_list[:12]\n\n # logger.info(\"Reading data from zms.\")\n # data_xds_list = xds_from_zarr(\"/home/jonathan/3C147_tests/3C147_daskms.zms\")\n\n # writes = xds_to_zarr(data_xds_list, \"/home/jonathan/3C147_tests/3C147_daskms.zms\")\n # dask.compute(writes)\n # return\n\n # Preprocess the xds_list - initialise some values and fix bad data.\n data_xds_list = preprocess_xds_list(data_xds_list, opts)\n\n # Model xds is a list of xdss onto which appropriate model data has been\n # assigned.\n data_xds_list = add_model_graph(data_xds_list, opts)\n\n # Adds the dask graph describing the calibration of the data.\n gain_xds_lol, data_xds_list = \\\n add_calibration_graph(data_xds_list, opts)\n\n if opts.flags_mad_enable:\n data_xds_list = add_mad_graph(data_xds_list, opts)\n\n writable_xds = finalise_flags(data_xds_list, opts)\n\n writes = write_xds_list(writable_xds, ref_xds_list, opts)\n\n gain_writes = write_gain_datasets(gain_xds_lol, opts)\n\n logger.success(\"{:.2f} seconds taken to build graph.\", time.time() - t0)\n\n if opts.parallel_scheduler == \"distributed\":\n # TODO: Dirty hack to coerce coordinate writes into graph. This should\n # should probably be handled by daskms.\n gain_writes = [dask.delayed(bool)(gw) for gw in gain_writes]\n\n t0 = time.time()\n\n with dask.distributed.performance_report(filename=\"cloning.html\"):\n\n dask.compute(writes, gain_writes,\n num_workers=opts.parallel_nthread,\n optimize_graph=True,\n scheduler=opts.parallel_scheduler)\n\n logger.success(\"{:.2f} seconds taken to execute graph.\", time.time() - t0)\n\n # dask.visualize([xds.MODEL_DATA.data for xds in data_xds_list], #writes,# gain_writes,\n # color='order', cmap='YlOrRd',\n # filename='order.pdf', node_attr={'penwidth': '4'},\n # optimize_graph=False,\n # collapse_outputs=False,\n # rankdir=\"BT\")\n\n # dask.visualize([xds.MODEL_DATA.data for xds in data_xds_list], #writes,# gain_writes,\n # filename='graph.pdf',\n # optimize_graph=False,\n # collapse_outputs=False,\n # rankdir=\"BT\")\n\n # dask.visualize(*gains_per_xds[\"G\"],\n # filename='gain_graph',\n # format=\"pdf\",\n # optimize_graph=True,\n # collapse_outputs=True,\n # node_attr={'penwidth': '4',\n # 'fontsize': '18',\n # 'fontname': 'helvetica'},\n # edge_attr={'penwidth': '2', })\n\n </pre>\n 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rows[np.lexsort([c.result() for c in sort_columns])]\n","self._condition.wait(timeout)\n","return rows[np.lexsort([c.result() for c in sort_columns])]\n","self._condition.wait(timeout)\n","return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args)))\n","result = _execute_task(task, cache)\n","return func(*(_execute_task(a, cache) for a in args))\n","return future.result()\n","self._condition.wait(timeout)\n","return func(*args, **kwargs)\n","idx = np.nonzero(diff != 1)[0]\n","","return _wrapfunc(a, 'nonzero')\n","","","","return _wrapreduction(a, np.logical_and, 'all', axis, None, out, keepdims=keepdims)\n","return np_spectral_model(stokes, spi[0], ref_freq, frequencies, base=base)\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._impl.rebuild(target_context, data)\n","return self._load_data(data_name)\n","return compiler.CompileResult._rebuild(target_context, *payload)\n","library = target_context.codegen().unserialize_library(libdata)\n","return self._library_class._unserialize(self, serialized)\n","self._codegen._engine._load_defined_symbols(self._shared_module)\n","for gsets in (mod.functions, mod.global_variables):\n","self.close()\n","self._dispose()\n","self._capi.LLVMPY_DisposeFunctionsIter(self)\n","baseptr = library.get_pointer_to_function(fndesc.llvm_func_name)\n","return self._codegen._engine.get_function_address(name)\n","return old(self._ee, *args, **kwargs)\n","return ffi.lib.LLVMPY_GetFunctionAddress(self, name.encode(\"ascii\"))\n","return (sig, codegen.magic_tuple(), (hasher(codebytes),\n","return (self._llvm_module.triple, self._get_host_cpu_name(),\n","return (ll.get_host_cpu_name()\n","ffi.lib.LLVMPY_GetHostCPUName(out)\n","result = _cm_type.__enter__(cm)\n","self.acquire()\n","return np_phase_delay(lm[0], uvw[0], frequency, convention=convention)\n","return_val = self.compile(tuple(argtypes))\n","scope.enter_context(global_compiler_lock)\n","result = _cm_type.__enter__(cm)\n","self.acquire()\n","return self._load_overload(sig, target_context)\n","data = self._cache_file.load(key)\n","overloads = self._load_index()\n","result = convert_impl(np_input, mapping, in_shape,\n","output[out_idx] = fn(input[c1_idx], input[c2_idx])\n","chunk = einsum(subscripts, *operands, dtype=dtype, **kwargs)\n","","","return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,\n","","return _wrapreduction(a, np.logical_and, 'all', axis, None, out, keepdims=keepdims)\n","return np_radec_to_lm(radec[0], phase_centre[0] if phase_centre else None)\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._impl.rebuild(target_context, data)\n","return self._load_data(data_name)\n","return compiler.CompileResult._rebuild(target_context, *payload)\n","cfunc = target_context.get_executable(library, fndesc, env)\n","return cfunc\n","envptr[0] = ctypes.c_void_p(id(env))\n","return old(self._ee, *args, **kwargs)\n","return ffi.lib.LLVMPY_GetGlobalValueAddress(self, name.encode(\"ascii\"))\n","result = _cm_type.__enter__(cm)\n","self.acquire()\n","return np_gaussian(uvw[0], frequency, shape_params[0])\n","return_val = self.compile(tuple(argtypes))\n","scope.enter_context(global_compiler_lock)\n","result = _cm_type.__enter__(cm)\n","self.acquire()\n","return np_parangles(t, ap[0], fc[0], **kw)\n","return casa_parallactic_angles(times,\n","return np.asarray([\n","reference_positions = [meas_serv.position(\n","return self.measure(loc, rf)\n","[ # Set antenna position as the reference frame\n","meas_serv.posangle(fc_rad, zenith).get_value(\"rad\")\n","or _measures.doframe(self, v):\n","return self.measure(loc, rf)\n","flags = flag_col | flag_row_col[:, None, None]\n","","return _wrapreduction(a, np.logical_or, 'any', axis, None, out, keepdims=keepdims)\n","table_proxy._ex.submit(fn, row_runs,\n","self._condition.wait(timeout)\n","zarray[selection] = data\n","self.set_basic_selection(selection, value, fields=fields)\n","return self._set_basic_selection_nd(selection, value, fields=fields)\n","self._set_selection(indexer, value, fields=fields)\n","self._chunk_setitems(lchunk_coords, lchunk_selection, chunk_values,\n","self._chunk_setitem_nosync(chunk_coords, chunk_selection, value,\n","self.chunk_store[ckey] = cdata\n","os.remove(temp_path)\n","return self._encode_chunk(chunk)\n","return self.__getitem__(item)\n","return Array(self._store, read_only=self._read_only, path=path,\n","self._load_metadata()\n","self._load_metadata_nosync()\n","meta_bytes = self._store[mkey]\n","if os.path.isfile(filepath):\n","return key in store\n","return os.path.isfile(file_path)\n","vis = np_predict_vis(time_index, antenna1, antenna2,\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._impl.rebuild(target_context, data)\n","return self._load_data(data_name)\n","return compiler.CompileResult._rebuild(target_context, *payload)\n","library = target_context.codegen().unserialize_library(libdata)\n","return self._library_class._unserialize(self, serialized)\n","self._finalize_final_module()\n","self._finalize_specific()\n","self._codegen._engine.finalize_object()\n","return old(self._ee, *args, **kwargs)\n","ffi.lib.LLVMPY_FinalizeObject(self)\n","result = _cm_type.__enter__(cm)\n","self.acquire()\n","return np_predict_vis(time_index, antenna1, antenna2,\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._cache_file.load(key)\n","overloads = self._load_index()\n","return compute_residual(data, model, gains, a1, a2, t_map_arr,\n","return_val = self.compile(tuple(argtypes))\n","cres = self._compiler.compile(args, return_type)\n","status, retval = self._compile_cached(args, return_type)\n","retval = self._compile_core(args, return_type)\n","cres = compiler.compile_extra(self.targetdescr.typing_context,\n","return pipeline.compile_extra(func)\n","return self._compile_bytecode()\n","return self._compile_core()\n","pm.run(self.state)\n","self._runPass(idx, pass_inst, state)\n","return func(*args, **kwargs)\n","mutated |= check(pss.run_pass, internal_state)\n","mangled = func(compiler_state)\n","find_literally_calls(state.func_ir, state.args)\n","raise errors.ForceLiteralArg(marked_args, loc=loc)\n","super(ForceLiteralArg, self).__init__(\n","new_msg = \"%s\\n%s\\n\" % (msg, loc.strformat())\n","lines = self.get_lines()\n","self.lines = linecache.getlines(self._get_path())\n","return updatecache(filename, module_globals)\n","return self._load_overload(sig, target_context)\n","data = self._cache_file.load(key)\n","overloads = self._load_index()\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._impl.rebuild(target_context, data)\n","return compiler.CompileResult._rebuild(target_context, *payload)\n","cfunc = target_context.get_executable(library, fndesc, env)\n","baseptr = library.get_pointer_to_function(fndesc.llvm_func_name)\n","return self._codegen._engine.get_function_address(name)\n","return old(self._ee, *args, **kwargs)\n","return ffi.lib.LLVMPY_GetFunctionAddress(self, name.encode(\"ascii\"))\n","return compute_corrected_residual(residual, gains, a1, a2, t_map_arr,\n","return_val = self._compile_for_args(*args)\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._cache_file.load(key)\n","overloads = self._load_index()\n","return compiler.CompileResult._rebuild(target_context, *payload)\n","cfunc = target_context.get_executable(library, fndesc, env)\n","baseptr = library.get_pointer_to_function(fndesc.llvm_func_name)\n","return self._codegen._engine.get_function_address(name)\n","return old(self._ee, *args, **kwargs)\n","return ffi.lib.LLVMPY_GetFunctionAddress(self, name.encode(\"ascii\"))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","key = self._index_key(sig, _get_codegen(target_context))\n","return (sig, codegen.magic_tuple(), (hasher(codebytes),\n","return (self._llvm_module.triple, self._get_host_cpu_name(),\n","return (ll.get_host_cpu_name()\n","ffi.lib.LLVMPY_GetHostCPUName(out)\n","overloads = self._load_index()\n","return func(*args, **kwargs)\n","values = self.func(*args, **kwargs)\n","","ret = _unique1d(ar, return_index, return_inverse, return_counts)\n","gain[..., (0, -1)] = 1 # Set first and last correlations to 1.\n","return_val = self.compile(tuple(argtypes))\n","cres = self._compiler.compile(args, return_type)\n","status, retval = self._compile_cached(args, return_type)\n","retval = self._compile_core(args, return_type)\n","cres = compiler.compile_extra(self.targetdescr.typing_context,\n","return pipeline.compile_extra(func)\n","return self._compile_bytecode()\n","return self._compile_core()\n","pm.run(self.state)\n","self._runPass(idx, pass_inst, state)\n","return func(*args, **kwargs)\n","mutated |= check(pss.run_pass, internal_state)\n","mangled = func(compiler_state)\n","find_literally_calls(state.func_ir, state.args)\n","raise errors.ForceLiteralArg(marked_args, loc=loc)\n","self.fold_arguments = fold_arguments\n","super(NumbaError, self).__init__(highlight(new_msg))\n","return tmp\n","return self.lines\n","return path\n","return join(*rel_list)\n","rewrites.rewrite_registry.apply('before-inference', state)\n","post_proc.run()\n","self._insert_var_dels()\n","return res\n","return analysis.compute_dead_maps(self.cfg, self._blocks, self.livemap,\n","return _dead_maps_result(internal=internal_dead_map,\n","config.reload_config()\n","_env_reloader.update()\n","self.old_environ = dict(new_environ)\n","return self._load_overload(sig, target_context)\n","key = self._index_key(sig, _get_codegen(target_context))\n","return (sig, codegen.magic_tuple(), (hasher(codebytes),\n","return (self._llvm_module.triple, self._get_host_cpu_name(),\n","return (ll.get_host_cpu_name()\n","return str(out)\n","self.close()\n","lib.LLVMPY_DisposeString(self._ptr)\n","return_val = self.compile(tuple(argtypes))\n","cres = self._cache.load_overload(sig, self.targetctx)\n","return self._load_overload(sig, target_context)\n","data = self._impl.rebuild(target_context, data)\n","return compiler.CompileResult._rebuild(target_context, *payload)\n","library = target_context.codegen().unserialize_library(libdata)\n","return self._library_class._unserialize(self, serialized)\n","self._shared_module = ll.parse_bitcode(shared_bitcode)\n","mod = ModuleRef(ffi.lib.LLVMPY_ParseBitcode(\n","baseptr = library.get_pointer_to_function(fndesc.llvm_func_name)\n","return self._codegen._engine.get_function_address(name)\n","return old(self._ee, *args, **kwargs)\n","return ffi.lib.LLVMPY_GetFunctionAddress(self, name.encode(\"ascii\"))\n","def _gc_callback(self, phase, info):\n","return fun(self)\n","return self._proc.memory_info()\n","return fun(self, *args, **kwargs)\n","with open_binary(\"%s/%s/statm\" % (self._procfs_path, self.pid)) as f:\n","return taql_proxy.getcol(\"__tablerow__\",\n","self._condition.wait(timeout)\n","ret = f(ret)\n","","return _wrapreduction(a, np.add, 'sum', axis, dtype, out, keepdims=keepdims,\n","return concatenate(arrays, axis=axes[0])\n","return concatenate3(transposelist(arrays, axes, 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